mirror of
https://github.com/Doctorado-ML/benchmark.git
synced 2025-08-16 16:05:54 +00:00
62 lines
2.0 KiB
Python
Executable File
62 lines
2.0 KiB
Python
Executable File
#! /usr/bin/env python
|
|
import os
|
|
from benchmark.Results import Summary
|
|
from benchmark.Utils import Folders, Files
|
|
from benchmark.Arguments import Arguments
|
|
|
|
"""List experiments of a model
|
|
"""
|
|
|
|
|
|
def main(args_test=None):
|
|
arguments = Arguments()
|
|
arguments.xset("number").xset("model", required=False).xset("key")
|
|
arguments.xset("hidden").xset("nan").xset("score", required=False)
|
|
arguments.xset("excel")
|
|
args = arguments.parse(args_test)
|
|
data = Summary(hidden=args.hidden)
|
|
data.acquire()
|
|
try:
|
|
data.list_results(
|
|
score=args.score,
|
|
model=args.model,
|
|
sort_key=args.key,
|
|
number=args.number,
|
|
)
|
|
is_test = args_test is not None
|
|
if not args.nan:
|
|
excel_generated = data.manage_results(args.excel, is_test)
|
|
if args.excel and excel_generated:
|
|
print(f"Generated file: {Files.be_list_excel}")
|
|
Files.open(Files.be_list_excel, is_test)
|
|
except ValueError as e:
|
|
print(e)
|
|
else:
|
|
if args.nan:
|
|
results_nan = []
|
|
results = data.get_results_criteria(
|
|
score=args.score,
|
|
model=args.model,
|
|
input_data=None,
|
|
sort_key=args.key,
|
|
number=args.number,
|
|
)
|
|
for result in results:
|
|
if result["metric"] != result["metric"]:
|
|
results_nan.append(result)
|
|
if results_nan != []:
|
|
print(
|
|
"\n"
|
|
+ "*" * 30
|
|
+ " Results with nan moved to hidden "
|
|
+ "*" * 30
|
|
)
|
|
data.data_filtered = []
|
|
data.list_results(input_data=results_nan)
|
|
for result in results_nan:
|
|
name = result["file"]
|
|
os.rename(
|
|
os.path.join(Folders.results, name),
|
|
os.path.join(Folders.hidden_results, name),
|
|
)
|