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import
sys
import
numpy
as
np
from
plasma
.
utils
.
performance
import
PerformanceAnalyzer
from
plasma
.
conf
import
conf
# mode = 'test'
file_num
=
0
save_figure
=
True
pred_ttd
=
False
T_min_warn
=
30
# None #take value from conf #30
verbose
=
False
if
len
(
sys
.
argv
)
>
1
:
results_dir
=
sys
.
argv
[
1
]
else
:
results_dir
=
conf
[
'paths'
][
'results_prepath'
]
shots_dir
=
conf
[
'paths'
][
'processed_prepath'
]
analyzer
=
PerformanceAnalyzer
(
conf
=
conf
,
results_dir
=
results_dir
,
shots_dir
=
shots_dir
,
i
=
file_num
,
T_min_warn
=
T_min_warn
,
verbose
=
verbose
,
pred_ttd
=
pred_ttd
)
analyzer
.
load_ith_file
()
P_thresh_opt
=
analyzer
.
compute_tradeoffs_and_print_from_training
()
# P_thresh_opt = 0.566 # 0.566 # 0.92
# analyzer.compute_tradeoffs_and_print_from_training()
linestyle
=
"-"
P_thresh_range
,
missed_range
,
fp_range
=
analyzer
.
compute_tradeoffs_and_plot
(
'test'
,
save_figure
=
save_figure
,
plot_string
=
'_test'
,
linestyle
=
linestyle
)
np
.
savez
(
'test_roc.npz'
,
"P_thresh_range"
,
P_thresh_range
,
"missed_range"
,
missed_range
,
"fp_range"
,
fp_range
)
analyzer
.
compute_tradeoffs_and_plot
(
'train'
,
save_figure
=
save_figure
,
plot_string
=
'_train'
,
linestyle
=
linestyle
)
analyzer
.
summarize_shot_prediction_stats_by_mode
(
P_thresh_opt
,
'test'
)
normalize
=
True
analyzer
.
example_plots
(
P_thresh_opt
,
'test'
,
'any'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'test'
, [
'FP'
],
extra_filename
=
'test'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'test'
, [
'FN'
],
extra_filename
=
'test'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'test'
, [
'TP'
],
extra_filename
=
'test'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'test'
, [
'late'
],
extra_filename
=
'test'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'train'
, [
'TN'
],
extra_filename
=
'train'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'train'
, [
'FP'
],
extra_filename
=
'train'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'train'
, [
'FN'
],
extra_filename
=
'train'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'train'
, [
'TP'
],
extra_filename
=
'train'
,
normalize
=
normalize
)
analyzer
.
example_plots
(
P_thresh_opt
,
'train'
, [
'late'
],
extra_filename
=
'train'
,
normalize
=
normalize
)
alarms
,
disr_alarms
,
nondisr_alarms
=
analyzer
.
gather_first_alarms
(
P_thresh_opt
,
'test'
)
analyzer
.
hist_alarms
(
disr_alarms
,
'disruptive alarms, P thresh = {}'
.
format
(
P_thresh_opt
),
save_figure
=
save_figure
,
linestyle
=
linestyle
)
np
.
savez
(
'disruptive_alarms_test.npz'
,
"disr_alarms"
,
disr_alarms
,
"P_thresh_opt"
,
P_thresh_opt
)
print
(
'{} disruptive alarms'
.
format
(
len
(
disr_alarms
)))
print
(
'{} seconds mean alarm time'
.
format
(
np
.
mean
(
disr_alarms
[
disr_alarms
>
0
])))
print
(
'{} seconds median alarm time'
.
format
(
np
.
median
(
disr_alarms
[
disr_alarms
>
0
])))
analyzer
.
hist_alarms
(
nondisr_alarms
,
'nondisruptive alarms, P thresh = {}'
.
format
(
P_thresh_opt
)
)
print
(
'{} nondisruptive alarms'
.
format
(
len
(
nondisr_alarms
)))
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