问如何在hdf5文件系统中创建组的属性并访问它们？

EN

import struct
import numpy as np
import h5py
import re

# First part generate convert the .gro -> .h5 .
csv_file = 'com'
fmtstring = '7s 8s 5s 7s 7s 7s'
fieldstruct = struct.Struct(fmtstring)
parse = fieldstruct.unpack_from

#define a np.dtype for gro array/dataset (hard-coded for now)
gro_dt = np.dtype([('col1', 'S7'), ('col2', 'S8'), ('col3', int), 
                   ('col4', float), ('col5', float), ('col6', float)])

with open(csv_file, 'r') as f, \
    h5py.File('xaa.h5', 'w') as hdf:

    # open group for position data
    particles_grp = hdf.require_group('particles/lipids/positions')
    h5md_grp = hdf.require_group('h5md/version/author/creator')
    h5md_grp.attrs['version'] = 1.0
    # datasets with known sizes
    ds_time = particles_grp.create_dataset('time', dtype="f", shape=(0,), maxshape=(None,), compression='gzip', shuffle=True)
    ds_step = particles_grp.create_dataset('step', dtype=np.uint64, shape=(0,), maxshape=(None,), compression='gzip', shuffle=True)
    ds_value = None

    step = 0
    while True:
        header = f.readline()
        m = re.search("t= *(.*)$", header)
        if m:
            time = float(m.group(1))
        else:
            print("End Of File")
            break

        # get number of data rows, i.e., number of particles
        nparticles = int(f.readline())
        # read data lines and store in array
        arr = np.empty(shape=(nparticles, 3), dtype=np.float32)
        for row in range(nparticles):
            fields = parse( f.readline().encode('utf-8') )
#            arr[row]['col1'] = fields[0].strip()            
#            arr[row]['col2'] = fields[1].strip()            
#            arr[row]['col3'] = int(fields[2])
            arr[row] = np.array((float(fields[3]), float(fields[4]), float(fields[5])))

        if nparticles > 0:
            # create a resizable dataset upon the first iteration
            if not ds_value:
                ds_value = particles_grp.create_dataset('value', dtype=np.float32,
                                                        shape=(0, nparticles, 3), maxshape=(None, nparticles, 3),
                                                        chunks=(1, nparticles, 3), compression='gzip', shuffle=True)

            # append this sample to the datasets
            ds_time.resize(step + 1, axis=0)
            ds_step.resize(step + 1, axis=0)
            ds_value.resize(step + 1, axis=0)

            ds_time[step] = time
            ds_step[step] = step
            ds_value[step] = arr

            #particles_grp[f'dataset_{step:04}'] = ds
            #ds= hdf.create_dataset(f'dataset_{step:04}', data=arr,compression='gzip') 
            #create attributes for this dataset / time step
#            hdr_tokens = header.split()
            #particles_grp['ds'] = ds
            #particles_grp[f'dataset_{step:04}'] = ds
#            ds.attrs['raw_header'] = header
            #ds.attrs['Generated by'] = hdr_tokens[2]
            #ds.attrs['P/L'] = hdr_tokens[4].split('=')[1]
#            ds.attrs['Time'] = hdr_tokens[6]

        footer = f.readline()
        step += 1


        #=============================================================================

with h5py.File('xaa.h5', 'r') as ff:
    base_items = list(ff.keys())
    print('Items in the base directory: ', base_items)
    value = ff.get('h5md/version')
    #dataset = np.array(value)
    #print("The shape of the value", value.shape)
    print(value.get_id('h5md/version/'))
    #print(list(ff.attrs.keys()))