generic.py 文件源码

def to_hdf5(self, hf, df, **kwargs):
        """
        Add datasets to a group for an HDF5 file handler
        """
        if self.dielectronic:
            grp_name = '/'.join([self.element, self.ion_name, 'dielectronic', self.filetype])
        else:
            grp_name = '/'.join([self.element, self.ion_name, self.filetype])
        if grp_name not in hf:
            grp = hf.create_group(grp_name)
            grp.attrs['chianti_version'] = df.meta['chianti_version']
            grp.attrs['footer'] = df.meta['footer']
        else:
            grp = hf[grp_name]
        hf['/'.join([self.element, self.ion_name])].attrs['element'] = self.element
        hf['/'.join([self.element, self.ion_name])].attrs['ion'] = self.ion_name
        for name in df.colnames:
            col = df[name]
            if type(col) == u.Quantity:
                data = col.value
            else:
                data = col.data
            if '<U' in data.dtype.str:
                numchar = data.dtype.str[2:]
                data = data.astype('|S{}'.format(numchar))
            if name in grp:
                ds = grp[name]
            else:
                if data.dtype == np.dtype('O'):
                    ragged_dtype = h5py.special_dtype(vlen=np.dtype('float64'))
                    ds = grp.create_dataset(name, data=data, dtype=ragged_dtype)
                else:
                    ds = grp.create_dataset(name, data=data, dtype=data.dtype)
            if col.unit is None:
                ds.attrs['unit'] = 'SKIP'
            else:
                ds.attrs['unit'] = col.unit.to_string()
            ds.attrs['description'] = df.meta['descriptions'][name]