[sktime]

data.py

print(df_long.head(3)) # longじゃない

sample  index      x     y      z                     time
0  2021-11-01 13:40:17.429      0 -0.912 0.369 -0.031  2021-11-01 13:40:17.429
1  2021-11-01 13:40:17.429      1 -0.908 0.363 -0.039  2021-11-01 13:40:17.529
2  2021-11-01 13:40:17.429      2 -0.910 0.363 -0.037  2021-11-01 13:40:17.629

# sktime形式に変更
# - sample(フレーム)毎に,groupbyして、行毎にシリーズに変更

df_train = df_long.groupby(["sample"]).apply(lambda x: pd.Series([x["x"], x["y"], x["z"]]) )

df_train

Dockerfile

FROM python:3.8-buster as builder

RUN pip3 install --upgrade pip
RUN pip3 install sktime==0.11.0

FROM python:3.8-slim-buster as runner

COPY --from=builder /usr/local/lib/python3.8/site-packages /usr/local/lib/python3.8/site-packages

RUN apt-get update \
    && apt-get install -y locales  locales-all\
    && locale-gen ja_JP.UTF-8 \
    && apt install -y libxml2 libgomp1\
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/*

ENV TZ Asia/Tokyo
ENV LANG ja_JP.UTF-8
ENV LC_ALL ja_JP.UTF-8
ENV LANGUAGE ja_JP.UTF-8



# ----------------------------------------------------------------------------------------------
ENV NUMBA_CPU_NAME=generic
RUN python3 -c "import sktime; print(sktime.__version__)"
RUN python3 -c "import sktime; from sktime.transformations.panel.rocket import MiniRocketMultivariate"
RUN python3 -c "import sktime; from sktime.transformations.panel.rocket import MiniRocketMultivariate"

ENTRYPOINT ["python3"]
CMD ["-m" "import sktime; from sktime.transformations.panel.rocket import MiniRocketMultivariate"]

UWaveGestureLibrary.py

BASE_DIR = f"/content/drive/MyDrive/workspace/datasets/sktime/"
!mkdir -p {BASE_DIR}

!wget http://www.timeseriesclassification.com/Downloads/UWaveGestureLibrary.zip
!unzip UWaveGestureLibrary.zip -d {BASE_DIR}/UWaveGestureLibrary

!pip install sktime[all_extras] -qq
import sktime
print(sktime.__version__)


import os
import sktime
from sktime.datasets import load_from_tsfile_to_dataframe

DATA_PATH = BASE_DIR

train_x, train_y = load_from_tsfile_to_dataframe(
    os.path.join(DATA_PATH, "UWaveGestureLibrary/UWaveGestureLibrary_TRAIN.ts")
)
test_x, test_y = load_from_tsfile_to_dataframe(
    os.path.join(DATA_PATH, "UWaveGestureLibrary/UWaveGestureLibrary_TEST.ts")
)

from sktime.datatypes._panel._convert import from_nested_to_3d_numpy

X_ary = from_nested_to_3d_numpy(train_x)
test_x_ary = from_nested_to_3d_numpy(test_x)

import numpy as np
np.save(f"{BASE_DIR}/UWaveGestureLibrary/train_x.npy", X_ary)
np.save(f"{BASE_DIR}/UWaveGestureLibrary/train_y.npy", train_y)
np.save(f"{BASE_DIR}/UWaveGestureLibrary/test_x.npy", test_x_ary)
np.save(f"{BASE_DIR}/UWaveGestureLibrary/test_y.npy", test_y)

assert len(X_ary) == len(train_y)
assert len(test_x_ary) == len(test_y)


X_ary = np.load(f"{BASE_DIR}/UWaveGestureLibrary/train_x.npy")
train_y = np.load(f"{BASE_DIR}/UWaveGestureLibrary/train_y.npy")
test_x_ary = np.load(f"{BASE_DIR}/UWaveGestureLibrary/test_x.npy")
test_y = np.load(f"{BASE_DIR}/UWaveGestureLibrary/test_y.npy")


assert len(X_ary) == len(train_y)
assert len(test_x_ary) == len(test_y)