Getting started with HDF5 widgets

Silx provides an implementation of a tree model and a tree view for HDF5 files. The aim of this tree is to provide a convenient read-only widget supporting file formats often used in synchrotrons for big amounts of data.

This page displays some source code to explain how to use this widget.

Commented source code

Import and create your tree view

HDF5 widgets are all exposed by the package silx.gui.hdf5.

import silx.gui.hdf5
treeview = silx.gui.hdf5.Hdf5TreeView()

Custom your tree view

The tree view can be customised to be sorted by default.

# Sort content of files by time or name
treeview.setSortingEnabled(True)

The model can be customised to support mouse interaction. A convenient method, i.e., Hdf5TreeView.findHdf5TreeModel(), returns the main HDF5 model used through proxy models.

model = treeview.findHdf5TreeModel()

# Avoid the user to drop file in the widget
model.setFileDropEnabled(False)

# Allow the user to reorder files with drag-and-drop
model.setFileMoveEnabled(True)

The tree view is also provided with a custom header that helps to choose visible columns.

header = treeview.header()

# Select displayed columns
column_ids = [treeview.findHdf5TreeModel().NAME_COLUMN]
header.setSections(column_ids)

# Do not allow the user to custom visible columns
header.setEnableHideColumnsPopup(False)

Add a file by name

The model can be used to add an HDF5 file. It is internally using silx.io.open().

model.insertFile("test.h5")

Add a file using h5py

The model internally uses the h5py object API. We can use directly h5py Files, Groups and Datasets.

import h5py
h5 = h5py.File("test.h5")

# We can use file
model.insertH5pyObject(h5)

# or group or dataset
model.insertH5pyObject(h5["group1"])
model.insertH5pyObject(h5["group1/dataset50"])

Add a file using silx

Silx also provides an input API and supports HDF5 files through h5py.

import silx.io

# We can load HDF5 files
model.insertH5pyObject(silx.io.open("test.h5"))

# or Spec files
model.insertH5pyObject(silx.io.open("test.dat"))

Custom context menu

The Hdf5TreeView provides a callback API to populate the context menu. The callback receives a Hdf5ContextMenuEvent every time the user requests the context menu. The event contains H5Node objects which wrap h5py objects adding extra information.

def my_action_callback(obj):
   # do what you want
   pass

def my_callback(event):
   objects = list(event.source().selectedH5Nodes())
   obj = objects[0]  # for single selection

   menu = event.menu()
   if obj.ntype is h5py.Dataset:
      action = qt.QAction("My funky action on datasets only", menu)
      action.triggered.connect(lambda: my_action_callback(obj))
      menu.addAction(action)

treeview.addContextMenuCallback(my_callback)

Capture selection

The Hdf5TreeView widget provides default Qt signals inherited from QAbstractItemView.

• activated:

  This signal is emitted when the item specified by index is activated by the user. How to activate items depends on the platform, e.g., by single- or double-clicking the item, or by pressing the Return or Enter key when the item is the current one.

• clicked:

  This signal is emitted when a mouse button is clicked. The item selected by mouse click is specified by index. The signal is only emitted when the index is a valid one.

• doubleClicked:

  This signal is emitted when a mouse button is double-clicked. The selected item is specified by index. The signal is only emitted when the index is a valid one.

• entered:

  This signal is emitted when the mouse cursor enters the item specified by index. Mouse tracking needs to be enabled for this feature to work.

• pressed:

  This signal is emitted when a mouse button is pressed. The selected item is specified by index. The signal is only emitted when the index is a valid one.

The method Hdf5TreeView.selectedH5Nodes() returns an iterator of H5Node objects which wrap h5py objects adding extra information.

def my_callback(index):
    objects = list(treeview.selectedH5Nodes())
    obj = objects[0]  # for single selection

    print(obj)

    print(obj.basename)             # not provided by h5py
    print(obj.name)
    print(obj.file.filename)

    print(obj.local_basename)       # not provided by h5py
    print(obj.local_name)           # not provided by h5py
    print(obj.local_file.filename)  # not provided by h5py

    print(obj.attrs)

    if obj.ntype is h5py.Dataset:
        print(obj.dtype)
        print(obj.shape)
        print(obj.value)        # create a copy of data of the dataset
        print(obj.h5py_object)  # reference to the Hdf5 dataset (or group)

treeview.clicked.connect(my_callback)

Example

The hdf5widget.py sample code provides an example of properties of the view, model and header.

Source code: hdf5widget.py.

After installing silx and downloading the script, you can run it from the command line prompt:

python hdf5widget.py <files>

This example loads files added to the command line, or files dropped from the file system. It also provides a GUI to display dummy test files.