tslearn/conftest.py at main · tslearn-team/tslearn · GitHub

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import warnings

import pytest

from tslearn.backend import check_keras_backend
from tslearn.datasets import UCR_UEA_datasets

try:
    check_keras_backend()
    import keras
except ImportError:
    keras = None


def pytest_ignore_collect(collection_path, *args, **kwargs):
    if keras is None and "shapelets" in collection_path.parts:
        return True


def pytest_collection_modifyitems(config, items):
    try:
        import pandas
    except ImportError:
        pandas = None

    try:
        import cesium
    except ImportError:
        cesium = None

    try:
        import torch
    except:
        torch = None

    if torch is None:
        skip_marker = pytest.mark.skip(reason="torch not installed!")
        for item in items:
            if item.name in [
                "tslearn.metrics._dtw.dtw",
                "tslearn.metrics.dtw_variants.dtw",
                "tslearn.metrics.softdtw_variants.cdist_soft_dtw_normalized",
                "tslearn.metrics.softdtw_variants.soft_dtw",
                "tslearn.metrics.softdtw_variants.soft_dtw_alignment",
                "tslearn.metrics.softdtw_variants.cdist_soft_dtw",
                "tslearn.metrics._frechet.frechet"
            ]:
                item.add_marker(skip_marker)
    if pandas is None:
        skip_marker = pytest.mark.skip(reason="pandas not installed!")
        for item in items:
            if item.name in [
                "tslearn.utils.cast.from_tsfresh_dataset",
                "tslearn.utils.cast.to_tsfresh_dataset",
                "tslearn.utils.cast.from_sktime_dataset",
                "tslearn.utils.cast.to_sktime_dataset",
                "tslearn.utils.cast.from_pyflux_dataset",
                "tslearn.utils.cast.to_pyflux_dataset",
                "tslearn.utils.cast.from_cesium_dataset",
                "tslearn.utils.cast.to_cesium_dataset",
            ]:
                item.add_marker(skip_marker)
    if cesium is None:
        skip_marker = pytest.mark.skip(reason="cesium not installed!")
        for item in items:
            if item.name in [
                "tslearn.utils.cast.to_cesium_dataset",
                "tslearn.utils.cast.from_cesium_dataset",
            ]:
                item.add_marker(skip_marker)

    # Skip related doctests if UCR UEA datasets cannot be fetched
    try:
        datasets = UCR_UEA_datasets()
        ucr_uea_datasets = bool(datasets.list_datasets())
    except Exception as exc:
        ucr_uea_datasets = False
        warnings.warn("Error listing UCR UEA datasets: {}".format(exc))

    if not ucr_uea_datasets:
        warnings.warn("Skipping doctests requiring UCR UEA dataset download")
        skip_marker = pytest.mark.skip(reason="Datasets not cached!")
        for item in items:
            if item.name in [
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.list_datasets",
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.list_multivariate_datasets",
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.list_univariate_datasets",
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.load_dataset",
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.baseline_accuracy",
                "tslearn.datasets.ucr_uea.UCR_UEA_datasets.list_cached_datasets"
            ]:
                item.add_marker(skip_marker)