from abc import ABC, abstractmethod
import copy
[docs]class Dataset(ABC):
"""Abstract base class for datasets."""
@abstractmethod
def __init__(self, **kwargs):
self.metadata = kwargs.pop('metadata', dict()) or dict()
self.metadata.update({
'transformer': '{}.__init__'.format(type(self).__name__),
'params': kwargs,
'previous': []
})
self.validate_dataset()
[docs] def validate_dataset(self):
"""Error checking and type validation."""
pass
[docs] def copy(self, deepcopy=False):
"""Convenience method to return a copy of this dataset.
Args:
deepcopy (bool, optional): :func:`~copy.deepcopy` this dataset if
`True`, shallow copy otherwise.
Returns:
Dataset: A new dataset with fields copied from this object and
metadata set accordingly.
"""
cpy = copy.deepcopy(self) if deepcopy else copy.copy(self)
# preserve any user-created fields
cpy.metadata = cpy.metadata.copy()
cpy.metadata.update({
'transformer': '{}.copy'.format(type(self).__name__),
'params': {'deepcopy': deepcopy},
'previous': [self]
})
return cpy
[docs] @abstractmethod
def export_dataset(self):
"""Save this Dataset to disk."""
raise NotImplementedError
[docs] @abstractmethod
def split(self, num_or_size_splits, shuffle=False):
"""Split this dataset into multiple partitions.
Args:
num_or_size_splits (array or int): If `num_or_size_splits` is an
int, *k*, the value is the number of equal-sized folds to make
(if *k* does not evenly divide the dataset these folds are
approximately equal-sized). If `num_or_size_splits` is an array
of type int, the values are taken as the indices at which to
split the dataset. If the values are floats (< 1.), they are
considered to be fractional proportions of the dataset at which
to split.
shuffle (bool, optional): Randomly shuffle the dataset before
splitting.
Returns:
list(Dataset): Splits. Contains *k* or `len(num_or_size_splits) + 1`
datasets depending on `num_or_size_splits`.
"""
raise NotImplementedError