ElectricityTiny#
- class capymoa.datasets.ElectricityTiny[source]#
Bases:
DownloadARFFGzip
A truncated version of the Electricity dataset with 1000 instances.
This is a tiny version (2k instances) of the Electricity widely used dataset described by M. Harries. This should only be used for quick tests, not for benchmarking algorithms.
See
Electricity
for the widely used electricity dataset.- __init__(
- directory: str = PosixPath('data'),
- auto_download: bool = True,
- CLI: str | None = None,
- schema: str | None = None,
Construct a Stream from a MOA stream object.
Usually, you will want to construct a Stream using the
capymoa.stream.stream_from_file()
function.- Parameters:
moa_stream – The MOA stream object to read instances from. Is None if the stream is created from a numpy array.
schema – The schema of the stream. If None, the schema is inferred from the moa_stream.
CLI – Additional command line arguments to pass to the MOA stream.
- Raises:
ValueError – If no schema is provided and no moa_stream is provided.
ValueError – If command line arguments are provided without a moa_stream.
- __iter__() Iterator[_AnyInstance] [source]#
Get an iterator over the stream.
This will NOT restart the stream if it has already been iterated over. Please use the
restart()
method to restart the stream.- Yield:
An iterator over the stream.
- __next__() _AnyInstance [source]#
Get the next instance in the stream.
- Returns:
The next instance in the stream.
- download(working_directory: Path) Path [source]#
Download the dataset and return the path to the downloaded dataset within the working directory.
- Parameters:
working_directory – The directory to download the dataset to.
- Returns:
The path to the downloaded dataset within the working directory.
- extract(stream_archive: Path) Path [source]#
Extract the dataset from the archive and return the path to the extracted dataset.
- Parameters:
stream_archive – The path to the archive containing the dataset.
- Returns:
The path to the extracted dataset.