b4e3e536c43812a4aa1c9f320c36124178d1a2bd,lore/encoders.py,Discrete,__init__,#Discrete#Any#Any#Any#Any#,294

Before Change

        self.__range = float("nan")
        self.missing_value = self.__norm + 1
        self.zero = 0
        if self.cardinality() < 2**8:
            self.dtype = numpy.uint8
        elif self.cardinality() < 2**16:
            self.dtype = numpy.uint16
        elif self.cardinality() < 2**32:
            self.dtype = numpy.uint32
        elif self.cardinality() < 2**64:
            self.dtype = numpy.uint64
        else:
            raise OverflowError("Woah, partner. That"s a lot of bins!")

    def fit(self, data):
        with timer(("fit %s:" % self.name), logging.DEBUG):
            series = self.series(data)
            self.__min = series.min()

After Change

        self.__range = float("nan")
        self.missing_value = self.__norm + 1
        self.zero = 0
        self.dtype = self._type_from_cardinality()

    def fit(self, data):
        with timer(("fit %s:" % self.name), logging.DEBUG):
            series = self.series(data)

Instances