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Xavier Garrido
CAMEL
Commits
60eba629
Commit
60eba629
authored
Dec 01, 2016
by
perdereau
Browse files
Merge branch 'master' of
https://gitlab.in2p3.fr/cosmotools/CAMEL
ndent pbs
parents
0338a016
533f81d2
Changes
1
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62 additions
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7 deletions
+62
-7
work/tools/python/camel.py
work/tools/python/camel.py
+62
-7
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work/tools/python/camel.py
View file @
60eba629
...
...
@@ -540,9 +540,10 @@ def hist2d( chain, par1, par2, *args, **kwargs):
H
=
nd
.
gaussian_filter
(
H
,
nsmooth
)
npts
=
5.
plt
.
imshow
(
H
.
T
,
origin
=
'bottom'
,
**
kwargs
)
plt
.
xticks
(
np
.
arange
(
npts
+
1
)
/
npts
*
bins
,[
"%4.2f"
%
i
for
i
in
np
.
linspace
(
extent
[
0
][
0
],
extent
[
0
][
1
],
npts
+
1
)])
plt
.
yticks
(
np
.
arange
(
npts
+
1
)
/
npts
*
bins
,[
"%4.2f"
%
i
for
i
in
np
.
linspace
(
extent
[
1
][
0
],
extent
[
1
][
1
],
npts
+
1
)])
# plt.imshow( H.T, origin='bottom', **kwargs)
# plt.xticks(np.arange(npts+1)/npts*bins,["%4.2f" % i for i in np.linspace(extent[0][0],extent[0][1],npts+1)])
# plt.yticks(np.arange(npts+1)/npts*bins,["%4.2f" % i for i in np.linspace(extent[1][0],extent[1][1],npts+1)])
plt
.
pcolormesh
(
X
,
Y
,
H
.
T
,
**
kwargs
)
plt
.
xlabel
(
parname
.
get
(
par1
,
par1
))
plt
.
ylabel
(
parname
.
get
(
par2
,
par2
))
...
...
@@ -1345,6 +1346,23 @@ class prof:
v
,
p
=
self
.
get
()
self
.
_p
=
p
self
.
ymin
=
min
(
p
)
def
write
(
self
,
filename
):
params
=
[
self
.
parname
]
+
list
(
np
.
extract
(
self
.
_params
(
self
.
_s
[
0
])
!=
self
.
parname
,
self
.
_params
(
self
.
_s
[
0
])))
param_line
=
" "
.
join
(
params
)
+
"
\n
"
f
=
open
(
filename
,
'w'
)
f
.
write
(
param_line
)
# print(param_line)
for
val
in
self
.
_s
:
data
=
self
.
_point_minimum
(
val
)
# print( " ".join([str(data[p]) for p in params]))
f
.
write
(
" "
.
join
([
str
(
data
[
p
])
for
p
in
params
])
+
"
\n
"
)
f
.
close
()
def
_writeBestFit
(
self
,
dir
,
f
):
#Extract Bestfit from logfile
...
...
@@ -1387,7 +1405,26 @@ class prof:
newf
.
close
()
def
point_minimum
(
self
,
val
,
verbose
=
False
):
def
point_allfits
(
self
,
val
,
par
=
'chi2'
):
"""
Get all fit chi2 at a given value from multi-Minimize runs
"""
import
os
path
,
dirs
,
files
=
os
.
walk
(
"%s/%s_%s"
%
(
self
.
dbdir
,
self
.
parname
,
val
)).
next
()
files
=
[
f
for
f
in
files
if
f
.
startswith
(
"best"
)]
nmin
=
len
(
files
)
allfits
=
[]
for
f
in
np
.
sort
(
files
):
#read all parameters
fname
=
"%s/%s_%s/%s"
%
(
self
.
dbdir
,
self
.
parname
,
val
,
f
)
if
os
.
stat
(
fname
).
st_size
!=
0
:
bftmp
=
read_bestfit
(
"%s/%s_%s/%s"
%
(
self
.
dbdir
,
self
.
parname
,
val
,
f
))
allfits
.
append
(
bftmp
[
par
])
return
(
allfits
)
def
_point_minimum
(
self
,
val
,
verbose
=
False
):
"""
Get minimum at a given value from multi-Minimize runs
"""
...
...
@@ -1412,7 +1449,24 @@ class prof:
bf
=
bftmp
return
(
bf
)
def
_params
(
self
,
val
):
"""
Returns list of parameters in the fit
"""
import
os
path
,
dirs
,
files
=
os
.
walk
(
"%s/%s_%s"
%
(
self
.
dbdir
,
self
.
parname
,
val
)).
next
()
files
=
[
f
for
f
in
files
if
f
.
startswith
(
"best"
)]
#read all parameters
fname
=
"%s/%s_%s/%s"
%
(
self
.
dbdir
,
self
.
parname
,
val
,
files
[
0
])
f
=
open
(
fname
,
'r'
)
params
=
np
.
array
(
f
.
readline
().
split
(),
dtype
=
str
)
return
(
params
)
def
get
(
self
,
par
=
'chi2'
):
"""
Return profile likelihood
...
...
@@ -1429,9 +1483,10 @@ class prof:
"""
p
=
[]
for
val
in
self
.
_s
:
p
.
append
(
self
.
point_minimum
(
val
)[
par
])
p
.
append
(
self
.
_
point_minimum
(
val
)[
par
])
return
(
self
.
_v
,
p
)
def
fit
(
self
,
method
=
'cubic'
,
order
=
3
,
deltaMax
=
np
.
inf
,
upper
=
False
,
CL
=
None
,
bounds
=
None
):
"""
Fit the profile with different models
...
...
@@ -1583,7 +1638,7 @@ class prof:
if
extent
==
None
:
extent
=
(
self
.
_v
[
0
],
self
.
_v
[
-
1
])
ax
.
plot
(
self
.
_v
,
self
.
_p
-
self
.
ymin
,
'ok'
,
color
=
color
,
marker
=
marker
)
ax
.
plot
(
self
.
_v
,
self
.
_p
-
self
.
ymin
,
color
=
color
,
marker
=
marker
,
linestyle
=
''
)
ax
.
set_xlabel
(
parname
.
get
(
self
.
_nameforclass
,
self
.
_nameforclass
),
fontsize
=
fontsize
)
ax
.
set_ylabel
(
"$\chi^2-\chi^2_{min}$"
,
fontsize
=
fontsize
)
...
...
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