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Gregory Ashton
PyFstat
Commits
724d6950
Commit
724d6950
authored
Aug 21, 2017
by
Gregory Ashton
Committed by
Gregory Ashton
Aug 21, 2017
Browse files
Fixes plotting det stat histogram and update timing coefficients
parent
bb17752e
Changes
1
Hide whitespace changes
Inline
Side-by-side
pyfstat/mcmc_based_searches.py
View file @
724d6950
...
...
@@ -372,13 +372,25 @@ class MCMCSearch(core.BaseSearchClass):
return
sampler
def
_estimate_run_time
(
self
):
tau0S
=
2.7e-8
tau0LD
=
1.6e-7
""" Print the estimated run time
Uses timing coefficients based on a Lenovo T460p Intel(R)
Core(TM) i5-6300HQ CPU @ 2.30GHz.
"""
# Todo: add option to time on a machine, and move coefficients to
# ~/.pyfstat.conf
if
(
type
(
self
.
theta_prior
[
'Alpha'
])
==
dict
or
type
(
self
.
theta_prior
[
'Delta'
])
==
dict
):
tau0S
=
7.3e-5
tau0LD
=
4.2e-7
else
:
tau0S
=
5.0e-5
tau0LD
=
6.2e-8
Nsfts
=
(
self
.
maxStartTime
-
self
.
minStartTime
)
/
1800.
average_numb_evals
=
np
.
sum
(
self
.
nsteps
)
*
self
.
nwalkers
*
self
.
ntemps
a
=
tau0S
*
Nsfts
*
average_numb_evals
b
=
tau0LD
*
Nsfts
*
average_numb_evals
print
(
a
,
b
,
Nsfts
)
numb_evals
=
np
.
sum
(
self
.
nsteps
)
*
self
.
nwalkers
*
self
.
ntemps
a
=
tau0S
*
numb_evals
b
=
tau0LD
*
Nsfts
*
numb_evals
logging
.
info
(
'Estimated run-time = {} s = {:1.0f}:{:1.0f} m'
.
format
(
a
+
b
,
*
divmod
(
a
+
b
,
60
)))
...
...
@@ -993,18 +1005,20 @@ class MCMCSearch(core.BaseSearchClass):
if
burnin_idx
and
add_det_stat_burnin
:
burn_in_vals
=
lnl
[:,
:
burnin_idx
].
flatten
()
try
:
axes
[
-
1
].
hist
(
burn_in_vals
[
~
np
.
isnan
(
burn_in_vals
)],
bins
=
50
,
histtype
=
'step'
,
color
=
'C3'
)
twoF_burnin
=
(
burn_in_vals
[
~
np
.
isnan
(
burn_in_vals
)]
-
self
.
likelihoodcoef
)
axes
[
-
1
].
hist
(
twoF_burnin
,
bins
=
50
,
histtype
=
'step'
,
color
=
'C3'
)
except
ValueError
:
logging
.
info
(
'Det. Stat. hist failed, most likely all '
'values where the same'
)
pass
else
:
burn
_
in
_vals
=
[]
twoF_
burnin
=
[]
prod_vals
=
lnl
[:,
burnin_idx
:].
flatten
()
try
:
axes
[
-
1
].
hist
(
prod_vals
[
~
np
.
isnan
(
prod_vals
)]
,
bins
=
50
,
histtype
=
'step'
,
color
=
'k'
)
twoF
=
prod_vals
[
~
np
.
isnan
(
prod_vals
)]
-
self
.
likelihoodcoef
axes
[
-
1
].
hist
(
twoF
,
bins
=
50
,
histtype
=
'step'
,
color
=
'k'
)
except
ValueError
:
logging
.
info
(
'Det. Stat. hist failed, most likely all '
'values where the same'
)
...
...
@@ -1014,7 +1028,7 @@ class MCMCSearch(core.BaseSearchClass):
else
:
axes
[
-
1
].
set_xlabel
(
r
'$\widetilde{2\mathcal{F}}$'
)
axes
[
-
1
].
set_ylabel
(
r
'$\textrm{Counts}$'
)
combined_vals
=
np
.
append
(
burn
_
in
_vals
,
prod_vals
)
combined_vals
=
np
.
append
(
twoF_
burnin
,
twoF
)
if
len
(
combined_vals
)
>
0
:
minv
=
np
.
min
(
combined_vals
)
maxv
=
np
.
max
(
combined_vals
)
...
...
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