https://github.com/rossant/h5view

Command-line tool in Python to explore a HDF5 file
https://github.com/rossant/h5view

Last synced: 9 months ago
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Command-line tool in Python to explore a HDF5 file

• Host: GitHub
• URL: https://github.com/rossant/h5view
• Owner: rossant
• License: other
• Created: 2012-12-30T15:24:02.000Z (about 13 years ago)
• Default Branch: master
• Last Pushed: 2015-11-13T11:52:56.000Z (about 10 years ago)
• Last Synced: 2025-03-24T04:51:40.788Z (10 months ago)
• Language: Python
• Size: 158 KB
• Stars: 19
• Watchers: 5
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
H5View: a light, h5py/IPython-friendly HDF5 viewer in text mode

===============================================================

This light Python module lets you explore interactively any HDF5 file in

a Python console or in IPython. Pretty print the file structure and get the

shape, data type, and size of any dataset. Tab completion works in IPython

to let you access any subgroup or dataset.

H5View is based on the h5py package.

Usage

-----

    import h5view

    with h5view.open('test.h5') as f:

        # display the whole structure of the file

        print(f)

        # access a group and display its information

        print(f.MyGroup1.SubGroup)

        # access a dataset

        X = f.MyGroup2.MyDataset[0,:]

        # access an attribute

        val = f.MyGroup3.myAttr

        # access to the corresponding h5py object

        item = f.MyDataset.item()

        # get a descendant from its relative path

        print(f.MyGroup4.get('MySubgroup/MyDataset'))

In IPython, tab completion shows all direct children (groups, datasets,

attributes) of the file or any item (group/dataset), making it quite

convenient to interactively explore a HDF5 file.

Installation

------------

The code is only in `h5view.py`. The `create.py` file is used to create

a test HDF5 file.

Download the package and type in a shell (a test HDF5 file is created

automatically in the same folder):

    $ python h5view.py

    Let's display the file.

    

    /

      * MyAttr: 23.0

    /MyGroup1

      * MyAttr2: my string

    /MyGroup1/MyGroup11

    /MyGroup1/MyGroup11/MyGroup111

    /MyGroup1/MyGroup11/MyGroup111/MyDataset2: shape (2, 3, 4, 5), dtype "float32", 480 B

    /MyGroup2

    /MyGroup2/MyDataset1: shape (100, 100), dtype "int32", 39.1 KB

    Now, let's access some attributes, groups, and datasets.

    23.0

    /MyGroup2

    /MyGroup2/MyDataset1: shape (100, 100), dtype "int32", 39.1 KB

    [[42 42]

     [42 42]]

    [ 0.  0.]