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Jörg Martin
vpvc_sample_size
Commits
e6e68a8e
Commit
e6e68a8e
authored
4 years ago
by
Jörg Martin
Browse files
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Plain Diff
Expanded uncertainties added
parent
71bd85b2
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Changes
3
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3 changed files
vpvc_algorithm/ssd_framework.py
+33
-0
33 additions, 0 deletions
vpvc_algorithm/ssd_framework.py
vpvc_gui.py
+0
-1
0 additions, 1 deletion
vpvc_gui.py
vpvc_interface/resultmenu.py
+51
-20
51 additions, 20 deletions
vpvc_interface/resultmenu.py
with
84 additions
and
21 deletions
vpvc_algorithm/ssd_framework.py
+
33
−
0
View file @
e6e68a8e
...
@@ -156,6 +156,19 @@ class poi_ssd_framework(generic_ssd_framework):
...
@@ -156,6 +156,19 @@ class poi_ssd_framework(generic_ssd_framework):
post_std
=
np
.
sqrt
(
self
.
alpha
+
n
*
mean
)
/
(
self
.
beta
+
n
)
post_std
=
np
.
sqrt
(
self
.
alpha
+
n
*
mean
)
/
(
self
.
beta
+
n
)
return
post_mean
,
post_std
return
post_mean
,
post_std
def
get_post_quantiles
(
self
,
mean
,
n
):
"""
Returns the median, lower_expanded_uncertainty, and upper_expanded_uncertainty given the sufficient statistic `mean` and the sample size `n`.
"""
post_alpha
=
self
.
alpha
+
mean
post_beta
=
self
.
beta
+
n
ppf
=
lambda
q
:
scipy
.
stats
.
gamma
.
ppf
(
q
,
a
=
post_alpha
)
/
post_beta
median
=
ppf
(
0.5
)
lower_expanded_uncertainty
=
median
-
ppf
(
0.025
)
upper_expanded_uncertainty
=
ppf
(
0.975
)
-
median
return
median
,
lower_expanded_uncertainty
,
upper_expanded_uncertainty
class
normal_ssd_framework
(
generic_ssd_framework
):
class
normal_ssd_framework
(
generic_ssd_framework
):
"""
"""
...
@@ -236,3 +249,23 @@ class normal_ssd_framework(generic_ssd_framework):
...
@@ -236,3 +249,23 @@ class normal_ssd_framework(generic_ssd_framework):
+
n
/
(
lamb
*
n_lamb
**
2
*
n_alpha
)
*
(
mean
-
mu_0
)
**
2
+
n
/
(
lamb
*
n_lamb
**
2
*
n_alpha
)
*
(
mean
-
mu_0
)
**
2
)
)
return
post_mean
,
post_std
return
post_mean
,
post_std
def
get_post_quantiles
(
self
,
mean
,
std
,
n
):
"""
Returns the median, lower expanded uncertainty, and upper expanded uncertainty given the sufficient statistics `mean`, `std` and the sample size `n`.
**Note**: For compatability both, lower and upper expanded_uncertainty are specified although they are identical for the Student t marginal.
"""
# use post mean and std
post_mean
,
post_std
=
self
.
make_inference
(
mean
,
std
,
n
)
# compute median
median
=
post_mean
# compute expanded uncertainty
post_alpha
=
self
.
alpha
+
n
/
2
df
=
2
*
post_alpha
std_t
=
np
.
sqrt
(
df
/
(
df
-
2
))
expansion_factor
=
scipy
.
stats
.
t
.
ppf
(
0.975
,
df
=
df
)
/
std_t
expanded_uncertainty
=
post_std
*
expansion_factor
lower_expanded_uncertainty
=
expanded_uncertainty
upper_expanded_uncertainty
=
expanded_uncertainty
return
median
,
lower_expanded_uncertainty
,
upper_expanded_uncertainty
This diff is collapsed.
Click to expand it.
vpvc_gui.py
+
0
−
1
View file @
e6e68a8e
...
@@ -8,4 +8,3 @@ from vpvc_interface.gui import run_gui
...
@@ -8,4 +8,3 @@ from vpvc_interface.gui import run_gui
run_gui
(
fontsize
=
11
)
run_gui
(
fontsize
=
11
)
This diff is collapsed.
Click to expand it.
vpvc_interface/resultmenu.py
+
51
−
20
View file @
e6e68a8e
...
@@ -153,28 +153,45 @@ class InferenceMenu():
...
@@ -153,28 +153,45 @@ class InferenceMenu():
self
.
stat_entries
=
(
self
.
mean_entry
,
)
self
.
stat_entries
=
(
self
.
mean_entry
,
)
self
.
computation_frame
=
tk
.
Frame
(
self
.
master
)
self
.
computation_frame
=
tk
.
Frame
(
self
.
master
)
self
.
compute_button
=
tk
.
Button
(
self
.
computation_frame
,
self
.
compute_button
=
tk
.
Button
(
self
.
computation_frame
,
text
=
button_text
,
command
=
lambda
:
self
.
compute_inference
(
ssd
))
text
=
button_text
,
command
=
lambda
:
self
.
compute_inference
(
ssd
,
distribution_name
))
self
.
compute_button
.
grid
(
row
=
0
,
column
=
0
,
sticky
=
tk
.
W
)
self
.
compute_button
.
grid
(
row
=
0
,
column
=
0
,
sticky
=
tk
.
W
)
self
.
estimate_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
width
=
3
0
,
bd
=
0
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
estimate_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
width
=
5
0
,
bd
=
0
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
uncertainty_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
bd
=
0
,
width
=
3
0
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
uncertainty_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
bd
=
0
,
width
=
5
0
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
estimate_text
.
grid
(
row
=
1
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
estimate_text
.
grid
(
row
=
1
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
uncertainty_text
.
grid
(
row
=
2
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
uncertainty_text
.
grid
(
row
=
2
,
column
=
0
,
sticky
=
tk
.
E
)
# quantiles of the posterior
if
distribution_name
==
'
Normal
'
:
self
.
expanded_uncertainty_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
bd
=
0
,
width
=
50
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
expanded_uncertainty_text
.
grid
(
row
=
3
,
column
=
0
,
sticky
=
tk
.
E
)
if
distribution_name
==
'
Poisson
'
:
self
.
median_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
width
=
50
,
bd
=
0
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
upper_expanded_uncertainty_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
bd
=
0
,
width
=
50
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
lower_expanded_uncertainty_text
=
tk
.
Text
(
self
.
computation_frame
,
height
=
1
,
bd
=
0
,
width
=
50
,
font
=
self
.
font
,
state
=
'
disabled
'
)
self
.
median_text
.
grid
(
row
=
3
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
lower_expanded_uncertainty_text
.
grid
(
row
=
4
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
upper_expanded_uncertainty_text
.
grid
(
row
=
5
,
column
=
0
,
sticky
=
tk
.
E
)
self
.
entry_frame
.
grid
(
row
=
0
,
column
=
0
,
sticky
=
tk
.
W
)
self
.
entry_frame
.
grid
(
row
=
0
,
column
=
0
,
sticky
=
tk
.
W
)
self
.
computation_frame
.
grid
(
row
=
1
,
column
=
0
,
sticky
=
tk
.
W
)
self
.
computation_frame
.
grid
(
row
=
1
,
column
=
0
,
sticky
=
tk
.
W
)
def
compute_inference
(
self
,
ssd
):
def
compute_inference
(
self
,
ssd
,
distribution_name
):
# preliminiaries for pretty printing
## return the magnitude of a number
magnitude
=
lambda
x
:
np
.
floor
(
np
.
log10
(
np
.
abs
(
x
)))
## format string into pretty printing
def
pretty_string
(
prefix
,
x
):
mag_x
=
magnitude
(
x
)
if
mag_x
>
4
or
mag_x
<
-
4
:
return
prefix
+
'
%e
'
%
(
x
,)
else
:
return
prefix
+
'
%f
'
%
(
x
,)
# make inference
try
:
try
:
args
=
[
float
(
e
.
get
())
for
e
in
self
.
stat_entries
]
args
=
[
float
(
e
.
get
())
for
e
in
self
.
stat_entries
]
n
=
int
(
self
.
n_entry
.
get
())
n
=
int
(
self
.
n_entry
.
get
())
## posterior mean and std
estimate
,
uncertainty
=
ssd
.
make_inference
(
*
args
,
n
)
estimate
,
uncertainty
=
ssd
.
make_inference
(
*
args
,
n
)
if
estimate
!=
0
:
## median and expanded uncertainties
estimate_magnitude
=
np
.
floor
(
np
.
log10
(
np
.
abs
(
estimate
)))
median
,
lower_expanded_uncertainty
,
upper_expanded_uncertainty
=
ssd
.
get_post_quantiles
(
*
args
,
n
)
else
:
estimate_magnitude
=
0
if
uncertainty
!=
0
:
uncertainty_magnitude
=
np
.
floor
(
np
.
log10
(
uncertainty
))
else
:
uncertainty_magnitude
=
0
except
(
ValueError
,
AssertionError
):
except
(
ValueError
,
AssertionError
):
self
.
status_variable
.
set
(
'
Invalid values encountered
'
)
self
.
status_variable
.
set
(
'
Invalid values encountered
'
)
raise
ValueError
(
'
Invalid values encountered
'
)
raise
ValueError
(
'
Invalid values encountered
'
)
...
@@ -183,16 +200,30 @@ class InferenceMenu():
...
@@ -183,16 +200,30 @@ class InferenceMenu():
self
.
status_variable
.
set
(
'
Bayesian inference
'
)
self
.
status_variable
.
set
(
'
Bayesian inference
'
)
self
.
uncertainty_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
uncertainty_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
estimate_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
estimate_text
.
delete
(
"
1.0
"
,
tk
.
END
)
if
estimate_magnitude
>
4
or
estimate_magnitude
<
-
4
:
self
.
estimate_text
.
insert
(
tk
.
END
,
pretty_string
(
'
Estimate:
'
,
estimate
))
self
.
estimate_text
.
insert
(
tk
.
END
,
'
Estimate: %e
'
%
(
estimate
,
))
self
.
uncertainty_text
.
insert
(
tk
.
END
,
pretty_string
(
'
Uncertainty:
'
,
uncertainty
))
else
:
self
.
estimate_text
.
insert
(
tk
.
END
,
'
Estimate: %f
'
%
(
estimate
,
))
if
uncertainty_magnitude
>
4
or
uncertainty_magnitude
<
-
4
:
self
.
uncertainty_text
.
insert
(
tk
.
END
,
'
Uncertainty: %e
'
%
(
uncertainty
,
))
else
:
self
.
uncertainty_text
.
insert
(
tk
.
END
,
'
Uncertainty: %f
'
%
(
uncertainty
,
))
self
.
estimate_text
.
configure
(
state
=
'
disabled
'
)
self
.
estimate_text
.
configure
(
state
=
'
disabled
'
)
self
.
uncertainty_text
.
configure
(
state
=
'
disabled
'
)
self
.
uncertainty_text
.
configure
(
state
=
'
disabled
'
)
if
distribution_name
==
'
Normal
'
:
self
.
expanded_uncertainty_text
.
configure
(
state
=
'
normal
'
)
self
.
expanded_uncertainty_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
expanded_uncertainty_text
.
insert
(
tk
.
END
,
pretty_string
(
'
Expanded uncertainty:
'
,
upper_expanded_uncertainty
))
self
.
expanded_uncertainty_text
.
configure
(
state
=
'
disabled
'
)
if
distribution_name
==
'
Poisson
'
:
self
.
median_text
.
configure
(
state
=
'
normal
'
)
self
.
lower_expanded_uncertainty_text
.
configure
(
state
=
'
normal
'
)
self
.
upper_expanded_uncertainty_text
.
configure
(
state
=
'
normal
'
)
self
.
median_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
lower_expanded_uncertainty_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
upper_expanded_uncertainty_text
.
delete
(
"
1.0
"
,
tk
.
END
)
self
.
median_text
.
insert
(
tk
.
END
,
pretty_string
(
'
Median:
'
,
median
))
self
.
lower_expanded_uncertainty_text
.
insert
(
tk
.
END
,
pretty_string
(
'
L. exp. uncertainty:
'
,
lower_expanded_uncertainty
))
self
.
upper_expanded_uncertainty_text
.
insert
(
tk
.
END
,
pretty_string
(
'
U. exp. uncertainty:
'
,
upper_expanded_uncertainty
))
self
.
median_text
.
configure
(
state
=
'
disabled
'
)
self
.
lower_expanded_uncertainty_text
.
configure
(
state
=
'
disabled
'
)
self
.
upper_expanded_uncertainty_text
.
configure
(
state
=
'
disabled
'
)
class
ResultMenu
():
class
ResultMenu
():
...
...
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