You have to use the keys method. This will give you a List of unicode strings of your dataset and group names. For example: Datasetnames=hf.keys() Another gui based method would be to use HDFView. https://support.hdfgroup.org/products/java/release/download.html
Usually the message File signature not found indicates either: 1. Your file is corrupted. … is what I think is most likely. You said you’ve opened the files before. Maybe you forgot closing your file-handle which can corrupt the file. Try checking the file with the HDF5 utility h5debug (available on command line if you’ve … Read more
We use Python in conjunction with h5py, numpy/scipy and boost::python to do data analysis. Our typical datasets have sizes of up to a few hundred GBs. HDF5 advantages: data can be inspected conveniently using the h5view application, h5py/ipython and the h5* commandline tools APIs are available for different platforms and languages structure data using groups … Read more
You want to assign values, not create a dataset: f1 = h5py.File(file_name, ‘r+’) # open the file data = f1[‘meas/frame1/data’] # load the data data[…] = X1 # assign new values to data f1.close() # close the file To confirm the changes were properly made and saved: f1 = h5py.File(file_name, ‘r’) np.allclose(f1[‘meas/frame1/data’].value, X1) #True
You need to install libhdf5-dev to get the required header files. Just run sudo apt-get install libhdf5-dev and it should install it and its dependencies automatically. Don’t worry about the NumPy warning, it just means that the package developers are using an old version of the API, but everything will still work.
I have found a solution that seems to work! Have a look at this: incremental writes to hdf5 with h5py! In order to append data to a specific dataset it is necessary to first resize the specific dataset in the corresponding axis and subsequently append the new data at the end of the “old” nparray. … Read more
HDF5 Advantages: Organization, flexibility, interoperability Some of the main advantages of HDF5 are its hierarchical structure (similar to folders/files), optional arbitrary metadata stored with each item, and its flexibility (e.g. compression). This organizational structure and metadata storage may sound trivial, but it’s very useful in practice. Another advantage of HDF is that the datasets can … Read more
h5py provides a model of datasets and groups. The former is basically arrays and the latter you can think of as directories. Each is named. You should look at the documentation for the API and examples: http://docs.h5py.org/en/latest/quick.html A simple example where you are creating all of the data upfront and just want to save it … Read more