lorenzo.volpi
/
QuAcc
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

generators updated, cleaning

This commit is contained in:
Lorenzo Volpi 2024-04-05 17:22:59 +02:00
parent cb6d1c8f2a
commit af0f1c7085
3 changed files with 3 additions and 28 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
quacc/experiments/generators.py
View File

@ -67,9 +67,9 @@ def gen_bin_datasets(
"imdb", "imdb",
] ]
_RCV1 = [ _RCV1 = [
# "CCAT", "CCAT",
# "GCAT", "GCAT",
# "MCAT", "MCAT",
] ]
for dn in _IMDB: for dn in _IMDB:
dval = None if only_names else DP.imdb() dval = None if only_names else DP.imdb()

16
test_imdb_max_shift.py
View File

@ -1,16 +0,0 @@
import pandas as pd
from quacc.legacy.evaluation.report import DatasetReport
dr = DatasetReport.unpickle("output/main/imdb/imdb.pickle")
_data = dr.data(
metric="acc", estimators=["bin_sld_lr_mc", "bin_sld_lr_ne", "bin_sld_lr_c"]
)
d1 = _data.loc[((0.9, 0.1), (1.0, 0.0), slice(None)), :]
d2 = _data.loc[((0.1, 0.9), (0.0, 1.0), slice(None)), :]
dd = pd.concat([d1, d2], axis=0)
print(d1.to_numpy(), "\n", d1.mean(), "\n")
print(d2.to_numpy(), "\n", d2.mean(), "\n")
print(dd.to_numpy(), "\n", dd.mean(), "\n")

9
test_postprocess.py
View File

@ -1,9 +0,0 @@
from quacc.legacy.evaluation.report import DatasetReport
dr = DatasetReport.unpickle("output/main/imdb/imdb.pickle")
_estimators = ["sld_lr_gs", "bin_sld_lr_gs", "mul_sld_lr_gs", "m3w_sld_lr_gs"]
_data = dr.data(metric="acc", estimators=_estimators)
for idx, cr in zip(_data.index.unique(0), dr.crs[::-1]):
print(cr.train_prev)
print({k: v for k, v in cr.fit_scores.items() if k in _estimators})
print(_data.loc[(idx, slice(None), slice(None)), :])