2014年1月5日 · Writing to hdf5 file depends either on h5py or pytables (each has a different python API that sits on top of the hdf5 file specification). You should also take a look at other simple binary formats provided by numpy natively such as np.save , np.savez etc:

2015年1月27日 · import h5py # Open the HDF5 file in read mode file_path = 'your_file.h5' with h5py.File(file_path, 'r') as file: # Function to recursively print the HDF5 dataset hierarchy def print_hdf5_item(name, obj): # name is in path format like /group1/group2/dataset if isinstance(obj, h5py.Group): # Do something like creating a dictionary entry print(f ...

EDIT: You specified h5py in the question so thats what I answered, but worth mentioning that with scipy.io.loadmat you should be able to get the original variables converted to numpy equivalents (eg object arrays).

2022年4月30日 · This exactly resolves my problem with very concise code :) I guess isinstance(f[key], h5py.Dataset) could be better, in case f[key] is an instance which class is inherited from h5py.Dataset, though this probably rarely happens. –

2014年2月14日 · As far as I have understood, h5py's .value method reads an entire dataset and dumps it into an array, which is slow and discouraged (and should be generally replaced by [()]. The correct way is to use numpy-esque slicing. However, …

2021年5月11日 · h5py, uses dictionary syntax to access Group objects, and reads Datasets using NumPy syntax. (Note group objects are not Python dictionaries - just just "look" like them!) As you noted, the keys() are the NAMES of the objects (groups or datasets) at the root level of your file.

2020年11月3日 · For my purposes, installing h5py 3.4 did not work, but installing 2.1 did (I think the concrete package just needed 2.1 and ignored 3.4). Commands used: pip install <full path to downloaded .whl file, can be copied from file properties> pip install <wanted package, for me quiskit, for example>

2017年1月18日 · HDF5 has the concept of dimension scales, as explained on the HDF5 and h5py websites. However, the explanations both use terse or generic examples and so I don't really understand how to use dimension scales. Namely, given a dataset f['coordinates'] in some HDF5 file f = h5py.File('data.h5'):

2015年2月10日 · Of course, if you convert your h5 file in an array, it is easy to select rows, but the thing is : Can we remove rows without creating an array ?

2022年5月26日 · With just numpy, data[np.s_[0,:]] = 2 works fine, but I don't know what h5py is doing or what it's checking. A full traceback might help, or one of us could study the h5py code. The h5py examples use simpler 1d slices. I haven't used this read_direct, so can't tell you from experience what are the limits. –