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Fix deprecated features in pandas 2.0 #2160

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Merged
jeylau merged 1 commit into from
Apr 11, 2023
Merged

Fix deprecated features in pandas 2.0 #2160

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6 changes: 3 additions & 3 deletions deeplabcut/refine_training_dataset/outlier_frames.py
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Expand Up @@ -241,7 +241,7 @@ def extract_outlier_frames(
* ``'uncertain'`` looks for frames with confidence below p_bound
* ``'manual'`` launches a GUI from which the user can choose the frames
* ``'list'`` looks for user to provide a list of frame numbers to use, 'frames2use'. In this case, ``'extractionalgorithm'`` is forced to be ``'uniform.'``

frames2use: list[str], optional, default=None
If ``'outlieralgorithm'`` is ``'list'``, provide the list of frames here.

Expand Down Expand Up @@ -405,7 +405,7 @@ def extract_outlier_frames(
elif outlieralgorithm == "jump":
temp_dt = df_temp.diff(axis=0) ** 2
temp_dt.drop("likelihood", axis=1, level="coords", inplace=True)
sum_ = temp_dt.sum(axis=1, level=1)
sum_ = temp_dt.groupby(level="bodyparts", axis=1).sum()
ind = df_temp.index[(sum_ > epsilon**2).any(axis=1)].tolist()
Indices.extend(ind)
elif outlieralgorithm == "fitting":
Expand Down Expand Up @@ -440,7 +440,7 @@ def extract_outlier_frames(
else:
raise ValueError(f'outlieralgorithm {outlieralgorithm} not recognized!')

# Run always except when the outlieralgorithm == manual.
# Run always except when the outlieralgorithm == manual.
if not outlieralgorithm == "manual":
Indices = np.sort(list(set(Indices))) # remove repetitions.
print(
Expand Down
2 changes: 1 addition & 1 deletion examples/testscript.py
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Expand Up @@ -257,7 +257,7 @@ def make_frame(t):
print("RELABELING")
DF = pd.read_hdf(file, "df_with_missing")
DLCscorer = np.unique(DF.columns.get_level_values(0))[0]
DF.columns.set_levels([scorer.replace(DLCscorer, scorer)], level=0, inplace=True)
DF.columns = DF.columns.set_levels([scorer.replace(DLCscorer, scorer)], level=0)
DF = DF.drop("likelihood", axis=1, level=2)
DF.to_csv(
os.path.join(
Expand Down
2 changes: 1 addition & 1 deletion examples/testscript_multianimal.py
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Expand Up @@ -244,7 +244,7 @@
print("RELABELING")
DF = pd.read_hdf(file, "df_with_missing")
DLCscorer = np.unique(DF.columns.get_level_values(0))[0]
DF.columns.set_levels([scorer.replace(DLCscorer, SCORER)], level=0, inplace=True)
DF.columns = DF.columns.set_levels([scorer.replace(DLCscorer, SCORER)], level=0)
DF = DF.drop("likelihood", axis=1, level=3)
DF.to_csv(
os.path.join(
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5 changes: 2 additions & 3 deletions tests/test_crossvalutils.py
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Expand Up @@ -9,7 +9,7 @@
# Licensed under GNU Lesser General Public License v3.0
#
import numpy as np
import pickle
import pandas as pd
from deeplabcut.pose_estimation_tensorflow.lib import crossvalutils


Expand Down Expand Up @@ -98,8 +98,7 @@ def test_benchmark_paf_graphs_montblanc(evaluation_data_and_metadata_montblanc):
[BEST_GRAPH_MONTBLANC],
split_inds=[metadata["data"]["trainIndices"], metadata["data"]["testIndices"]],
)
with open("tests/data/montblanc_map.pickle", "rb") as file:
results_gt = pickle.load(file)
results_gt = pd.read_pickle("tests/data/montblanc_map.pickle")
np.testing.assert_equal(
results[1].loc["purity"].to_numpy().squeeze(),
results_gt[0].loc["purity", 6].to_numpy(),
Expand Down