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from abc import ABC, abstractmethod
import os
import attr
from so_magic.utils import Observer
@attr.s(str=True, repr=True)
class Dataset:
"""High level representation of data, of some form.
Instances of this class encapsulate observations in the form of datapoints
as well as their respective feature vectors. Feature vectors can then be
trivially "fed" into a Machine Learning algorithm (eg SOM).
Args:
datapoints ():
name (str, optional):
Returns:
[type]: [description]
"""
datapoints = attr.ib(init=True)
name = attr.ib(init=True, default=None)
_features = attr.ib(init=True, default=[])
size = attr.ib(init=False, default=attr.Factory(lambda self: len(self.datapoints) if self.datapoints else 0, takes_self=True))
@property
def features(self):
return self._features
@features.setter
def features(self, features):
self._features = features
boromir674 /
so-magic
