123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990 |
- """
- ================================
- Datasets (:mod:`scipy.datasets`)
- ================================
- .. currentmodule:: scipy.datasets
- Dataset Methods
- ===============
- .. autosummary::
- :toctree: generated/
- ascent
- face
- electrocardiogram
- Utility Methods
- ===============
- .. autosummary::
- :toctree: generated/
- download_all -- Download all the dataset files to specified path.
- clear_cache -- Clear cached dataset directory.
- Usage of Datasets
- =================
- SciPy dataset methods can be simply called as follows: ``'<dataset-name>()'``
- This downloads the dataset files over the network once, and saves the cache,
- before returning a `numpy.ndarray` object representing the dataset.
- Note that the return data structure and data type might be different for
- different dataset methods. For a more detailed example on usage, please look
- into the particular dataset method documentation above.
- How dataset retrieval and storage works
- =======================================
- SciPy dataset files are stored within individual github repositories under the
- SciPy GitHub organization, following a naming convention as
- ``'dataset-<name>'``, for example `scipy.datasets.face` files live at
- https://github.com/scipy/dataset-face. The `scipy.datasets` submodule utilizes
- and depends on `Pooch <https://www.fatiando.org/pooch/latest/>`_, a Python
- package built to simplify fetching data files. Pooch uses these repos to
- retrieve the respective dataset files when calling the dataset function.
- A registry of all the datasets, essentially a mapping of filenames with their
- SHA256 hash and repo urls are maintained, which Pooch uses to handle and verify
- the downloads on function call. After downloading the dataset once, the files
- are saved in the system cache directory under ``'scipy-data'``.
- Dataset cache locations may vary on different platforms.
- For macOS::
- '~/Library/Caches/scipy-data'
- For Linux and other Unix-like platforms::
- '~/.cache/scipy-data' # or the value of the XDG_CACHE_HOME env var, if defined
- For Windows::
- 'C:\\Users\\<user>\\AppData\\Local\\<AppAuthor>\\scipy-data\\Cache'
- In environments with constrained network connectivity for various security
- reasons or on systems without continuous internet connections, one may manually
- load the cache of the datasets by placing the contents of the dataset repo in
- the above mentioned cache directory to avoid fetching dataset errors without
- the internet connectivity.
- """
- from ._fetchers import face, ascent, electrocardiogram # noqa: E402
- from ._download_all import download_all
- from ._utils import clear_cache
- __all__ = ['ascent', 'electrocardiogram', 'face',
- 'download_all', 'clear_cache']
- from scipy._lib._testutils import PytestTester
- test = PytestTester(__name__)
- del PytestTester
|