What is an HDF file?
Some extracts from the HDF group tutorial:
Hierarchical Data Format 5 (HDF5) is a unique open source technology suite for managing data collections of all sizes and complexity.
HDF5 has features of other formats but it can do much more. HDF5 is similar to XML in that HDF5 files are self-describing and allow users to specify complex data relationships and dependencies. In contrast to XML documents, HDF5 files can contain binary data (in many representations) and allow direct access to parts of the file without first parsing the entire contents.
HDF5 also allows hierarchical data objects to be expressed in a natural manner (similar to directories and files), in contrast to the tables in a relational database. Whereas relational databases support tables, HDF5 supports n-dimensional datasets and each element in the dataset may itself be a complex object. Relational databases offer excellent support for queries based on field matching, but are not well-suited for sequentially processing all records in the database or for selecting a subset of the data based on coordinate-style lookup.
Editing the file
As discussed in the postprocessing documentation, it is possible to calculate a quantity at different conditions with the same moments of an expansion. In these case, one need to change some paramenters in the hdf file that are settings for the post-processing tool. By editing the .h5 files, we can change the temperature of a conductivity calculation or the number of points in energy that are wanted.
For that purpose, we provide a simple python script that rewrites specific parts of our .h5 files. As discussed above, the .h5 contains hierarchical data objects that are similar to the structure of directories and files.
When modifying a paramenter like temperature, we need to locate in the .h5 file the quantity that is going to be calculated and modify its temperature. The script describes how to list the parameters associated to each quantity and how to edit one parameter.
file_name = 'archive.h5' f = h5py.File(file_name, 'r+') # open the file # List all groups print('All groups') for key in f.keys(): # Names of the groups in HDF5 file. print(key) print() # Get the HDF5 group group = f['Calculation'] # Checkout what keys are inside that group. print('Single group') for key in group.keys(): print(key) print() #if you want to modify other quantity, check de list and change the subgroup below # Get the HDF5 subgroup subgroup = group['conductivity_dc'] # Checkout what keys are inside that subgroup. print('Subgroup') for key in subgroup.keys(): print(key) print() new_value = 70 data = subgroup['Temperature'] # load the data data[...] = new_value # assign new values to data f.close() # close the file # To confirm the changes were properly made and saved: f1 = h5py.File(file_name, 'r') print(np.allclose(f1['Calculation/conductivity_dc/Temperature'].value, new_value))