Reading multiple datasets in hdf5

I have an HDF5 file format where the datasets are in a group like /abc/xyz1 to /abc/xyznnn

All these have similar datasets: name, age, loc

How do I loop through these n subgroups to read all the data from the hdf5 file?

Answer 1

[Animesh]

Hello!

You can use MATLAB's h5info function to get information about the contents of the HDF5 file(including the names of the datasets and groups) and h5read to read the data from the dataset.

You can do something like this to read all the data from all subgroups of "/abc":

filename = 'yourfile.h5';
info = h5info(filename, '/abc');
subgroup_names = {info.Groups.Name};
for i = 1:length(subgroup_names)
    groupname = subgroup_names{i};
    name = h5read(filename, strcat(groupname, '/name'));
    age = h5read(filename, strcat(groupname, '/age'));
    loc = h5read(filename, strcat(groupname, '/loc'));
    % Do something with the data
end

You may refer to the following documentation for more information:

h5info: https://in.mathworks.com/help/matlab/ref/h5info.html

h5read: https://in.mathworks.com/help/matlab/ref/h5read.html

Answer 2

[David]

@ geometry dash lite

Hello, I think you can use the h5py library in Python. Here's an example of how you can achieve this:

import h5py

# Open the HDF5 file

file = h5py.File('your_file.hdf5', 'r')


# Get the group containing the subgroups

group = file['abc']


# Loop through the subgroups

for subgroup_name in group:
    
    subgroup = group[subgroup_name]
    
    # Access the datasets within the subgroup
    
    name = subgroup['name'][:]
    
    age = subgroup['age'][:]
    
    loc = subgroup['loc'][:]
    
    
    # Process the data as needed
    
    print(f"Subgroup: {subgroup_name}")
    
    print(f"Name: {name}")
    
    print(f"Age: {age}")
    
    print(f"Location: {loc}")
    
    
    # Close the HDF5 file
    
    file.close()

In this example, you first open the HDF5 file using h5py.File() and then access the group containing the subgroups using file['abc']. You can replace 'abc' with the actual name of your group.

Next, you iterate over the subgroups in the group using a for loop. For each subgroup, you access the datasets name, age, and loc by indexing into the subgroup object (subgroup['name'], subgroup['age'], subgroup['loc']). The [:] indexing is used to read the data from the datasets.

You can process the data within the loop as needed. In the example, I've simply printed the data, but you can perform any required operations or store the data in a suitable data structure.

Finally, don't forget to close the HDF5 file using file.close() to free up system resources.