column.py 文件源码

def __init__(self, arr=None, metadata=None, missing_id='<missing>',
                 groupings=None, substitute=True, weights=None, name=None):
        super(self.__class__, self).__init__(arr, metadata, missing_id=missing_id, weights=weights, name=name)
        self._nan = np.array([np.nan]).astype(int)[0]

        if substitute and metadata is None:
            self.arr, self.orig_type = self.substitute_values(self.arr)
        elif substitute and metadata and not np.issubdtype(self.arr.dtype, np.integer):
            # custom metadata has been passed in from external source, and must be converted to int
            self.arr = self.arr.astype(int)
            self.metadata = { int(k):v for k, v in metadata.items() }
            self.metadata[self._nan] = missing_id

        self._groupings = {}
        if groupings is None:
            for x in np.unique(self.arr):
                self._groupings[x] = [x, x + 1, False]
        else:
            for x in np.unique(self.arr):
                self._groupings[x] = list(groupings[x])
        self._possible_groups = None