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Iker Martín Álvarez
Proteo
Commits
794bf5a3
Commit
794bf5a3
authored
Apr 04, 2023
by
Iker Martín Álvarez
Browse files
Added Python code to create an iteration specific dataframe for analysis.
parent
52d63679
Changes
1
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Side-by-side
Analysis/CreateIterDataframe.py
0 → 100644
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794bf5a3
import
sys
import
glob
import
numpy
as
np
import
pandas
as
pd
from
enum
import
Enum
class
G_enum
(
Enum
):
TOTAL_RESIZES
=
0
TOTAL_GROUPS
=
1
TOTAL_STAGES
=
2
GRANULARITY
=
3
SDR
=
4
ADR
=
5
DR
=
6
RED_METHOD
=
7
RED_STRATEGY
=
8
SPAWN_METHOD
=
9
SPAWN_STRATEGY
=
10
GROUPS
=
11
FACTOR_S
=
12
DIST
=
13
STAGE_TYPES
=
14
STAGE_TIMES
=
15
STAGE_BYTES
=
16
ITERS
=
17
ASYNCH_ITERS
=
18
T_ITER
=
19
T_STAGES
=
20
T_SPAWN
=
21
T_SPAWN_REAL
=
22
T_SR
=
23
T_AR
=
24
T_TOTAL
=
25
#Malleability specific
NP
=
0
NC
=
1
#Iteration specific
IS_DYNAMIC
=
11
#columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
# "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Groups", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
# "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_total"] #26
#columnsM = ["NP", "NC", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
# "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "FactorS", "Dist", "Stage_Type", "Stage_Time", \
# "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR"] #24
columnsL
=
[
"NP"
,
"NC"
,
"Total_Stages"
,
"Granularity"
,
"SDR"
,
"ADR"
,
"DR"
,
"Redistribution_Method"
,
\
"Redistribution_Strategy"
,
"Spawn_Method"
,
"Spawn_Strategy"
,
"Is_Dynamic"
,
"FactorS"
,
"Dist"
,
"Stage_Types"
,
"Stage_Times"
,
\
"Stage_Bytes"
,
"Asynch_Iters"
,
"T_iter"
,
"T_stages"
]
#20
def
copy_iteration
(
row
,
dataL_it
,
group
,
iteration
,
is_asynch
):
basic_indexes
=
[
G_enum
.
TOTAL_STAGES
.
value
,
G_enum
.
GRANULARITY
.
value
,
\
G_enum
.
STAGE_TYPES
.
value
,
G_enum
.
STAGE_TIMES
.
value
,
G_enum
.
STAGE_BYTES
.
value
]
basic_asynch
=
[
G_enum
.
SDR
.
value
,
G_enum
.
ADR
.
value
,
G_enum
.
DR
.
value
]
array_asynch_group
=
[
G_enum
.
RED_METHOD
.
value
,
G_enum
.
RED_STRATEGY
.
value
,
\
G_enum
.
SPAWN_METHOD
.
value
,
G_enum
.
SPAWN_STRATEGY
.
value
]
dataL_it
[
G_enum
.
FACTOR_S
.
value
]
=
row
[
G_enum
.
FACTOR_S
.
value
][
group
]
dataL_it
[
G_enum
.
NP
.
value
]
=
row
[
G_enum
.
GROUPS
.
value
][
group
]
dataL_it
[
G_enum
.
DIST
.
value
]
=
[
None
,
None
]
dataL_it
[
G_enum
.
DIST
.
value
][
0
]
=
row
[
G_enum
.
DIST
.
value
][
group
]
dataL_it
[
G_enum
.
ASYNCH_ITERS
.
value
-
1
]
=
is_asynch
dataL_it
[
G_enum
.
T_ITER
.
value
-
1
]
=
row
[
G_enum
.
T_ITER
.
value
][
group
][
iteration
]
dataL_it
[
G_enum
.
T_STAGES
.
value
-
1
]
=
row
[
G_enum
.
T_STAGES
.
value
][
group
][
iteration
]
dataL_it
[
G_enum
.
IS_DYNAMIC
.
value
]
=
True
if
group
>
0
else
False
for
index
in
basic_indexes
:
dataL_it
[
index
]
=
row
[
index
]
if
is_asynch
:
dataL_it
[
G_enum
.
NC
.
value
]
=
row
[
G_enum
.
GROUPS
.
value
][
group
+
1
]
dataL_it
[
G_enum
.
DIST
.
value
][
1
]
=
row
[
G_enum
.
DIST
.
value
][
group
+
1
]
for
index
in
basic_asynch
:
dataL_it
[
index
]
=
row
[
index
]
for
index
in
array_asynch_group
:
dataL_it
[
index
]
=
row
[
index
][
group
+
1
]
#-----------------------------------------------
def
create_iter_dataframe
(
dfG
,
dataL
):
it
=
-
1
for
row_index
in
range
(
len
(
dfG
)):
row
=
dfG
.
iloc
[
row_index
]
groups
=
row
[
G_enum
.
TOTAL_GROUPS
.
value
]
for
group
in
range
(
groups
):
real_iterations
=
len
(
row
[
G_enum
.
T_ITER
.
value
][
group
])
real_asynch
=
row
[
G_enum
.
ASYNCH_ITERS
.
value
][
group
]
is_asynch
=
False
for
iteration
in
range
(
real_iterations
-
real_asynch
):
it
+=
1
dataL
.
append
(
[
None
]
*
len
(
columnsL
)
)
copy_iteration
(
row
,
dataL
[
it
],
group
,
iteration
,
is_asynch
)
is_asynch
=
True
for
iteration
in
range
(
real_iterations
-
real_asynch
,
real_iterations
):
it
+=
1
dataL
.
append
(
[
None
]
*
len
(
columnsL
)
)
copy_iteration
(
row
,
dataL
[
it
],
group
,
iteration
,
is_asynch
)
#-----------------------------------------------
if
len
(
sys
.
argv
)
<
2
:
print
(
"The files name is missing
\n
Usage: python3 CreateIterDataframe.py input_file.pkl output_name"
)
exit
(
1
)
input_name
=
sys
.
argv
[
1
]
if
len
(
sys
.
argv
)
>
2
:
name
=
sys
.
argv
[
2
]
else
:
name
=
"dataL"
print
(
"File name will be: "
+
name
+
".pkl"
)
dfG
=
pd
.
read_pickle
(
input_name
)
dataL
=
[]
create_iter_dataframe
(
dfG
,
dataL
)
dfL
=
pd
.
DataFrame
(
dataL
,
columns
=
columnsL
)
dfL
.
to_pickle
(
name
+
'.pkl'
)
#dfL.to_excel(name + '.xlsx')
print
(
dfG
)
print
(
dfL
)
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