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Kim Whoriskey
swim
Commits
40d92919
Commit
40d92919
authored
Sep 30, 2020
by
kimwhoriskey
Browse files
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Browse Files
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Plain Diff
better way of adding in the gps errors
parent
7dbf4836
Changes
6
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Showing
6 changed files
with
380 additions
and
41 deletions
+380
-41
src/dcrws_ssm_argos.hpp
src/dcrws_ssm_argos.hpp
+136
-0
src/dcrws_ssm_combo.hpp
src/dcrws_ssm_combo.hpp
+16
-12
src/dcrws_ssm_gps.hpp
src/dcrws_ssm_gps.hpp
+140
-0
src/likelihoods.hpp
src/likelihoods.hpp
+72
-23
src/swim.cpp
src/swim.cpp
+14
-4
src/trackstruct.hpp
src/trackstruct.hpp
+2
-2
No files found.
src/dcrws_ssm_argos.hpp
0 → 100644
View file @
40d92919
#undef TMB_OBJECTIVE_PTR
#define TMB_OBJECTIVE_PTR obj
using
namespace
density
;
template
<
class
Type
>
Type
dcrwSSMargos
(
objective_function
<
Type
>
*
obj
)
{
// data
// names of each track
vector
<
std
::
string
>
tracknames
=
StringList
(
"tracknames"
,
obj
);
int
ntracks
=
tracknames
.
size
();
vector
<
track
<
Type
>
>
tracks
(
ntracks
);
// vector< kind of element> name(size)
// tracks
for
(
int
i
=
0
;
i
<
ntracks
;
i
++
){
track
<
Type
>
indtrack
(
tracknames
[
i
],
obj
);
tracks
[
i
]
=
indtrack
;
}
REPORT
(
ntracks
);
// parameters
// Input parameters - i.e. parameters to estimate.
PARAMETER_VECTOR
(
working_theta
);
vector
<
Type
>
theta
(
2
);
theta
(
0
)
=
2
*
M_PI
/
(
1.0
+
exp
(
-
working_theta
(
0
)))
-
M_PI
;
// -pi to pi
theta
(
1
)
=
2
*
M_PI
/
(
1.0
+
exp
(
-
working_theta
(
1
)));
// 0 to 2pi
ADREPORT
(
theta
);
PARAMETER_VECTOR
(
working_gamma
);
vector
<
Type
>
gamma
(
2
);
gamma
(
0
)
=
1.0
/
(
1.0
+
exp
(
-
working_gamma
(
0
)));
gamma
(
1
)
=
gamma
(
0
)
/
(
1.0
+
exp
(
-
working_gamma
(
1
)));
ADREPORT
(
gamma
);
PARAMETER
(
working_sigma_lon
);
Type
sigma_lon
=
exp
(
working_sigma_lon
);
ADREPORT
(
sigma_lon
);
PARAMETER
(
working_sigma_lat
);
Type
sigma_lat
=
exp
(
working_sigma_lat
);
ADREPORT
(
sigma_lat
);
// Variance-covariance matrix for the process equation.
matrix
<
Type
>
Sigma
(
2
,
2
);
Sigma
<<
sigma_lon
*
sigma_lon
,
0.0
,
0.0
,
sigma_lat
*
sigma_lat
;
PARAMETER_MATRIX
(
working_A
);
//matrix of switching probabilities
int
m
=
working_A
.
rows
();
// number of states
matrix
<
Type
>
A
(
m
,
m
);
for
(
int
i
=
0
;
i
<
m
;
++
i
){
for
(
int
j
=
0
;
j
<
(
m
-
1
);
++
j
){
A
(
i
,
j
)
=
exp
(
working_A
(
i
,
j
));
//ensures the probabilities we estimate are >0
}
A
(
i
,
m
-
1
)
=
1.0
;
A
.
row
(
i
)
*=
1.0
/
A
.
row
(
i
).
sum
();
}
ADREPORT
(
A
);
// system of equations stat dist
matrix
<
Type
>
system
(
m
,
m
);
for
(
int
i
=
0
;
i
<
m
;
i
++
)
{
for
(
int
j
=
0
;
j
<
m
;
j
++
)
{
if
(
i
==
j
)
{
system
(
i
,
j
)
=
1
-
A
(
j
,
i
)
+
1
;
}
else
{
system
(
i
,
j
)
=
0
-
A
(
j
,
i
)
+
1
;
}
}
}
// vector of ones for stat dist
vector
<
Type
>
ones
(
m
);
for
(
int
i
=
0
;
i
<
m
;
i
++
)
{
ones
(
i
)
=
1.0
;
}
// take the inverse of the system matrix and then multiply by the vector of ones
matrix
<
Type
>
sys_inverse
=
system
.
inverse
();
vector
<
Type
>
delta
=
sys_inverse
*
ones
;
PARAMETER
(
working_psi
);
//working value for measurement error
Type
psi
=
exp
(
working_psi
);
ADREPORT
(
psi
);
// likelihood calculations
//Calculate logLikelihood
Type
nll
=
0.0
;
// behaviour equation
vector
<
Type
>
behav
(
ntracks
);
Type
tmpb
=
0.0
;
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpb
=
behaviour
(
tracks
[
i
].
b
,
delta
,
A
);
behav
(
i
)
=
tmpb
;
}
REPORT
(
behav
);
nll
-=
behav
.
sum
();
// movement equation
Type
tmpp
=
0.0
;
vector
<
Type
>
move
(
ntracks
);
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpp
=
movement
(
tracks
[
i
].
x
,
tracks
[
i
].
b
,
gamma
,
theta
,
Sigma
);
move
(
i
)
=
tmpp
;
}
REPORT
(
move
);
nll
+=
move
.
sum
();
// measurement equation
Type
tmpm
=
0.0
;
vector
<
Type
>
meas
(
ntracks
);
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpm
=
measurement_argos
(
tracks
[
i
].
y
,
tracks
[
i
].
x
,
tracks
[
i
].
idx
,
tracks
[
i
].
jidx
,
tracks
[
i
].
ae
,
psi
);
meas
(
i
)
=
tmpm
;
}
REPORT
(
meas
);
nll
+=
meas
.
sum
();
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
)
tracks
[
i
].
Rep
();
REPORT
(
nll
);
return
nll
;
}
#undef TMB_OBJECTIVE_PTR
#define TMB_OBJECTIVE_PTR this
src/dcrws_ssm.hpp
→
src/dcrws_ssm
_combo
.hpp
View file @
40d92919
...
...
@@ -5,7 +5,7 @@ using namespace density;
template
<
class
Type
>
Type
dcrwSSM
(
objective_function
<
Type
>
*
obj
)
{
Type
dcrwSSM
combo
(
objective_function
<
Type
>
*
obj
)
{
// data
...
...
@@ -82,15 +82,15 @@ Type dcrwSSM(objective_function<Type> * obj) {
matrix
<
Type
>
sys_inverse
=
system
.
inverse
();
vector
<
Type
>
delta
=
sys_inverse
*
ones
;
//
PARAMETER(working_psi); //working value for measurement error
//
Type psi = exp(working_psi);
//
ADREPORT(psi);
//
//
PARAMETER_VECTOR(working_gps_err); // working value for gps measurement error
//
vector<Type> gps_err = exp(working_gps_err);
//
matrix<Type> gpsSigma(2,2);
//
gpsSigma << gps_err(0)*gps_err(0), 0.0,
//
0.0, gps_err(1)*gps_err(1);
PARAMETER
(
working_psi
);
//working value for measurement error
Type
psi
=
exp
(
working_psi
);
ADREPORT
(
psi
);
PARAMETER_VECTOR
(
working_gps_err
);
// working value for gps measurement error
vector
<
Type
>
gps_err
=
exp
(
working_gps_err
);
matrix
<
Type
>
gpsSigma
(
2
,
2
);
gpsSigma
<<
gps_err
(
0
)
*
gps_err
(
0
),
0.0
,
0.0
,
gps_err
(
1
)
*
gps_err
(
1
);
...
...
@@ -124,9 +124,13 @@ Type dcrwSSM(objective_function<Type> * obj) {
// measurement equation
Type
tmpm
=
0.0
;
vector
<
Type
>
meas
(
ntracks
);
// for(int i=0; i < ntracks; ++i){
// int measdatatype=tracks[i].datatype(0);
// tmpm = measurement(obj, tracks[i].y, tracks[i].x, tracks[i].kind, tracks[i].idx, tracks[i].jidx, tracks[i].ae, measdatatype);
// meas(i) = tmpm;
// }
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
int
measdatatype
=
tracks
[
i
].
datatype
(
0
);
tmpm
=
measurement
(
obj
,
tracks
[
i
].
y
,
tracks
[
i
].
x
,
tracks
[
i
].
kind
,
tracks
[
i
].
idx
,
tracks
[
i
].
jidx
,
tracks
[
i
].
ae
,
measdatatype
);
tmpm
=
measurement_combo
(
tracks
[
i
].
y
,
tracks
[
i
].
x
,
tracks
[
i
].
kind
,
tracks
[
i
].
idx
,
tracks
[
i
].
jidx
,
tracks
[
i
].
ae
,
psi
,
gpsSigma
);
meas
(
i
)
=
tmpm
;
}
// for(int i=0; i < ntracks; ++i){
...
...
src/dcrws_ssm_gps.hpp
0 → 100644
View file @
40d92919
#undef TMB_OBJECTIVE_PTR
#define TMB_OBJECTIVE_PTR obj
using
namespace
density
;
template
<
class
Type
>
Type
dcrwSSMgps
(
objective_function
<
Type
>
*
obj
)
{
// data
// names of each track
vector
<
std
::
string
>
tracknames
=
StringList
(
"tracknames"
,
obj
);
int
ntracks
=
tracknames
.
size
();
vector
<
track
<
Type
>
>
tracks
(
ntracks
);
// vector< kind of element> name(size)
// tracks
for
(
int
i
=
0
;
i
<
ntracks
;
i
++
){
track
<
Type
>
indtrack
(
tracknames
[
i
],
obj
);
tracks
[
i
]
=
indtrack
;
}
REPORT
(
ntracks
);
// parameters
// Input parameters - i.e. parameters to estimate.
PARAMETER_VECTOR
(
working_theta
);
vector
<
Type
>
theta
(
2
);
theta
(
0
)
=
2
*
M_PI
/
(
1.0
+
exp
(
-
working_theta
(
0
)))
-
M_PI
;
// -pi to pi
theta
(
1
)
=
2
*
M_PI
/
(
1.0
+
exp
(
-
working_theta
(
1
)));
// 0 to 2pi
ADREPORT
(
theta
);
PARAMETER_VECTOR
(
working_gamma
);
vector
<
Type
>
gamma
(
2
);
gamma
(
0
)
=
1.0
/
(
1.0
+
exp
(
-
working_gamma
(
0
)));
gamma
(
1
)
=
gamma
(
0
)
/
(
1.0
+
exp
(
-
working_gamma
(
1
)));
ADREPORT
(
gamma
);
PARAMETER
(
working_sigma_lon
);
Type
sigma_lon
=
exp
(
working_sigma_lon
);
ADREPORT
(
sigma_lon
);
PARAMETER
(
working_sigma_lat
);
Type
sigma_lat
=
exp
(
working_sigma_lat
);
ADREPORT
(
sigma_lat
);
// Variance-covariance matrix for the process equation.
matrix
<
Type
>
Sigma
(
2
,
2
);
Sigma
<<
sigma_lon
*
sigma_lon
,
0.0
,
0.0
,
sigma_lat
*
sigma_lat
;
PARAMETER_MATRIX
(
working_A
);
//matrix of switching probabilities
int
m
=
working_A
.
rows
();
// number of states
matrix
<
Type
>
A
(
m
,
m
);
for
(
int
i
=
0
;
i
<
m
;
++
i
){
for
(
int
j
=
0
;
j
<
(
m
-
1
);
++
j
){
A
(
i
,
j
)
=
exp
(
working_A
(
i
,
j
));
//ensures the probabilities we estimate are >0
}
A
(
i
,
m
-
1
)
=
1.0
;
A
.
row
(
i
)
*=
1.0
/
A
.
row
(
i
).
sum
();
}
ADREPORT
(
A
);
// system of equations stat dist
matrix
<
Type
>
system
(
m
,
m
);
for
(
int
i
=
0
;
i
<
m
;
i
++
)
{
for
(
int
j
=
0
;
j
<
m
;
j
++
)
{
if
(
i
==
j
)
{
system
(
i
,
j
)
=
1
-
A
(
j
,
i
)
+
1
;
}
else
{
system
(
i
,
j
)
=
0
-
A
(
j
,
i
)
+
1
;
}
}
}
// vector of ones for stat dist
vector
<
Type
>
ones
(
m
);
for
(
int
i
=
0
;
i
<
m
;
i
++
)
{
ones
(
i
)
=
1.0
;
}
// take the inverse of the system matrix and then multiply by the vector of ones
matrix
<
Type
>
sys_inverse
=
system
.
inverse
();
vector
<
Type
>
delta
=
sys_inverse
*
ones
;
PARAMETER_VECTOR
(
working_gps_err
);
// working value for gps measurement error
vector
<
Type
>
gps_err
=
exp
(
working_gps_err
);
matrix
<
Type
>
gpsSigma
(
2
,
2
);
gpsSigma
<<
gps_err
(
0
)
*
gps_err
(
0
),
0.0
,
0.0
,
gps_err
(
1
)
*
gps_err
(
1
);
// likelihood calculations
//Calculate logLikelihood
Type
nll
=
0.0
;
// behaviour equation
vector
<
Type
>
behav
(
ntracks
);
Type
tmpb
=
0.0
;
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpb
=
behaviour
(
tracks
[
i
].
b
,
delta
,
A
);
behav
(
i
)
=
tmpb
;
}
REPORT
(
behav
);
nll
-=
behav
.
sum
();
// movement equation
Type
tmpp
=
0.0
;
vector
<
Type
>
move
(
ntracks
);
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpp
=
movement
(
tracks
[
i
].
x
,
tracks
[
i
].
b
,
gamma
,
theta
,
Sigma
);
move
(
i
)
=
tmpp
;
}
REPORT
(
move
);
nll
+=
move
.
sum
();
// measurement equation
Type
tmpm
=
0.0
;
vector
<
Type
>
meas
(
ntracks
);
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
){
tmpm
=
measurement_gps
(
tracks
[
i
].
y
,
tracks
[
i
].
x
,
tracks
[
i
].
idx
,
tracks
[
i
].
jidx
,
tracks
[
i
].
ae
,
gpsSigma
);
meas
(
i
)
=
tmpm
;
}
REPORT
(
meas
);
nll
+=
meas
.
sum
();
for
(
int
i
=
0
;
i
<
ntracks
;
++
i
)
tracks
[
i
].
Rep
();
REPORT
(
nll
);
return
nll
;
}
#undef TMB_OBJECTIVE_PTR
#define TMB_OBJECTIVE_PTR this
src/likelihoods.hpp
View file @
40d92919
...
...
@@ -43,29 +43,78 @@ Type movement(matrix<Type> x, vector<int> b, vector<Type> gamma, vector<Type> th
return
rslt
;
}
// // measurement process
// template<class Type>
// Type measurement(array<Type> y, matrix<Type> x, vector<int> idx, vector<Type> jidx, matrix<Type> ae, Type psi){
//
// vector<Type> measnll(y.cols());
// vector<Type> xhat(2);
// vector<Type> tmp(2);
// vector<Type> tmp2(2);
//
// for(int i = 0; i < y.cols(); ++i){
// xhat = (1.0-jidx(i)) * x.col(idx(i)-1) + jidx(i)*x.col(idx(i));
// tmp = y.col(i);
// tmp2 = tmp-xhat;
// // nll += nll_meas(tmp-xhat); //MVNORM_t returns the negative log likelihood
// // taken from Marie's DCRW_Argos.cpp file
// // dt returns the log likelihood
// measnll(i) = -(0.5*log(psi) - log(ae(i,0)) + dt(sqrt(psi)*tmp2(0)/ae(i,0),ae(i,1),true) ); // Longitude
// measnll(i) -= (0.5*log(psi) - log(ae(i,2)) + dt(sqrt(psi)*tmp2(1)/ae(i,2),ae(i,3),true) ); // Latitude
// }
//
// Type rslt = measnll.sum();
// return rslt; // negative log-lik
// }
// measurement process
template
<
class
Type
>
Type
measurement_argos
(
array
<
Type
>
y
,
matrix
<
Type
>
x
,
vector
<
int
>
idx
,
vector
<
Type
>
jidx
,
matrix
<
Type
>
ae
,
Type
psi
){
vector
<
Type
>
measnll
(
y
.
cols
());
vector
<
Type
>
xhat
(
2
);
vector
<
Type
>
tmp
(
2
);
vector
<
Type
>
tmp2
(
2
);
for
(
int
i
=
0
;
i
<
y
.
cols
();
++
i
){
xhat
=
(
1.0
-
jidx
(
i
))
*
x
.
col
(
idx
(
i
)
-
1
)
+
jidx
(
i
)
*
x
.
col
(
idx
(
i
));
tmp
=
y
.
col
(
i
);
tmp2
=
tmp
-
xhat
;
// nll += nll_meas(tmp-xhat); //MVNORM_t returns the negative log likelihood
// taken from Marie's DCRW_Argos.cpp file
// dt returns the log likelihood
measnll
(
i
)
=
-
(
0.5
*
log
(
psi
)
-
log
(
ae
(
i
,
0
))
+
dt
(
sqrt
(
psi
)
*
tmp2
(
0
)
/
ae
(
i
,
0
),
ae
(
i
,
1
),
true
)
);
// Longitude
measnll
(
i
)
-=
(
0.5
*
log
(
psi
)
-
log
(
ae
(
i
,
2
))
+
dt
(
sqrt
(
psi
)
*
tmp2
(
1
)
/
ae
(
i
,
2
),
ae
(
i
,
3
),
true
)
);
// Latitude
}
Type
rslt
=
measnll
.
sum
();
return
rslt
;
// negative log-lik
}
template
<
class
Type
>
Type
measurement_gps
(
array
<
Type
>
y
,
matrix
<
Type
>
x
,
vector
<
int
>
idx
,
vector
<
Type
>
jidx
,
matrix
<
Type
>
ae
,
matrix
<
Type
>
gpsSigma
){
vector
<
Type
>
measnll
(
y
.
cols
());
vector
<
Type
>
xhat
(
2
);
vector
<
Type
>
tmp
(
2
);
vector
<
Type
>
tmp2
(
2
);
density
::
MVNORM_t
<
Type
>
gps_nll
(
gpsSigma
);
for
(
int
i
=
0
;
i
<
y
.
cols
();
++
i
){
xhat
=
(
1.0
-
jidx
(
i
))
*
x
.
col
(
idx
(
i
)
-
1
)
+
jidx
(
i
)
*
x
.
col
(
idx
(
i
));
tmp
=
y
.
col
(
i
);
tmp2
=
tmp
-
xhat
;
measnll
(
i
)
=
gps_nll
(
tmp2
);
//MVNORM_t returns the negative log likelihood
}
Type
rslt
=
measnll
.
sum
();
return
rslt
;
// negative log-lik
}
template
<
class
Type
>
Type
measurement_combo
(
array
<
Type
>
y
,
matrix
<
Type
>
x
,
vector
<
int
>
kind
,
vector
<
int
>
idx
,
vector
<
Type
>
jidx
,
matrix
<
Type
>
ae
,
Type
psi
,
matrix
<
Type
>
gpsSigma
){
vector
<
Type
>
measnll
(
y
.
cols
());
vector
<
Type
>
xhat
(
2
);
vector
<
Type
>
tmp
(
2
);
vector
<
Type
>
tmp2
(
2
);
density
::
MVNORM_t
<
Type
>
gps_nll
(
gpsSigma
);
for
(
int
i
=
0
;
i
<
y
.
cols
();
++
i
){
xhat
=
(
1.0
-
jidx
(
i
))
*
x
.
col
(
idx
(
i
)
-
1
)
+
jidx
(
i
)
*
x
.
col
(
idx
(
i
));
tmp
=
y
.
col
(
i
);
tmp2
=
tmp
-
xhat
;
if
(
kind
(
i
)
==
0
){
measnll
(
i
)
=
gps_nll
(
tmp2
);
//MVNORM_t returns the negative log likelihood
}
else
if
(
kind
(
i
)
==
1
)
{
// taken from Marie's DCRW_Argos.cpp file
// dt returns the log likelihood
measnll
(
i
)
=
-
(
0.5
*
log
(
psi
)
-
log
(
ae
(
i
,
0
))
+
dt
(
sqrt
(
psi
)
*
tmp2
(
0
)
/
ae
(
i
,
0
),
ae
(
i
,
1
),
true
)
);
// Longitude
measnll
(
i
)
-=
(
0.5
*
log
(
psi
)
-
log
(
ae
(
i
,
2
))
+
dt
(
sqrt
(
psi
)
*
tmp2
(
1
)
/
ae
(
i
,
2
),
ae
(
i
,
3
),
true
)
);
// Latitude
}
}
Type
rslt
=
measnll
.
sum
();
return
rslt
;
// negative log-lik
}
//
...
...
src/swim.cpp
View file @
40d92919
...
...
@@ -5,13 +5,17 @@
#include "likelihoods.hpp"
#include "measlikelihood.hpp"
#include "dcrws_hmm.hpp"
#include "dcrws_ssm.hpp"
#include "dcrws_ssm_combo.hpp"
#include "dcrws_ssm_argos.hpp"
#include "dcrws_ssm_gps.hpp"
// map the data_integer to a character
enum
model_choices
{
dcrwhmm
=
0
,
dcrwssm
=
1
,
dcrwssmargos
=
1
,
dcrwssmgps
=
2
,
dcrwssmcombo
=
3
,
};
template
<
class
Type
>
...
...
@@ -24,8 +28,14 @@ switch(model){
case
dcrwhmm
:
return
dcrwHMM
(
this
);
break
;
case
dcrwssm
:
return
dcrwSSM
(
this
);
case
dcrwssmargos
:
return
dcrwSSMargos
(
this
);
break
;
case
dcrwssmgps
:
return
dcrwSSMgps
(
this
);
break
;
case
dcrwssmcombo
:
return
dcrwSSMcombo
(
this
);
break
;
}
}
src/trackstruct.hpp
View file @
40d92919
...
...
@@ -9,7 +9,7 @@ struct track {
array
<
Type
>
y
;
vector
<
int
>
b
;
vector
<
int
>
kind
;
vector
<
int
>
datatype
;
//
vector<int> datatype;
vector
<
int
>
idx
;
vector
<
Type
>
jidx
;
matrix
<
Type
>
ae
;
...
...
@@ -30,7 +30,7 @@ track<Type>::track(std::string name, objective_function<Type> *obj) { // objecti
y
=
tmbutils
::
asArray
<
Type
>
(
getListElement
(
tracking_data
,
"y"
));
b
=
asVector
<
int
>
(
getListElement
(
tracking_data
,
"b"
));
kind
=
asVector
<
int
>
(
getListElement
(
tracking_data
,
"kind"
));
datatype
=
asVector
<
int
>
(
getListElement
(
tracking_data
,
"datatype"
))
;
//
datatype = asVector<int>(getListElement(tracking_data, "datatype")) ;
idx
=
asVector
<
int
>
(
getListElement
(
tracking_data
,
"idx"
));
jidx
=
asVector
<
Type
>
(
getListElement
(
tracking_data
,
"jidx"
));
ae
=
asMatrix
<
Type
>
(
getListElement
(
tracking_data
,
"ae"
));
...
...
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