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#!/usr/bin/env python
import h5py
import numpy as np
import scipy as sp
import scipy.ndimage as spi
import matplotlib.pyplot as plt

Basic operations

Basic operations allows to access the dataset records from HDF5.

• Open file, get dataset, get array for current event, and close file:

    file    = h5py.File(hdf5_file_name, 'r')   # Open hdf5 file in read-only mode
    dataset = file[dataset_name]
    arr1ev  = dataset[event_number]
    file.close()

HDF5 file structure

Detailed desciption of the HDF5 file structure can be found in HDF5 or h5py
web sites. Breifly speaking, its structure resembles the file system directory tree. The top level of the HDF5 tree is a file;
file may contain groups and datasets; each group may contain other groups and datasets; each dataset contains the data objects, which in most cases can be associated with numpy types.
So, there are three type of items in HDF5 file: File, Group, and Dataset. Their names are used as an access keys.

Basic operations

Basic operations allows to access the dataset records from HDF5.
Here we assume that user knows explicitly the names of file and dataset and event number, for example

    hdf5_file_name = '/reg/d/psdm/XPP/xppcom10/hdf5/xppcom10-r0546.h5'
    dataset_name   = '/Configure:0000/Run:0000/CalibCycle:0000/Camera::FrameV1/XppSb4Pim.1:Tm6740.1/image'
    event_number   = 5

• Open file, get dataset, get array for current event, and close file:

    file    = h5py.File(hdf5_file_name, 'r')   # 'r' means that hdf5 file is open in read-only mode
    dataset = file[dataset_name]
    arr1ev  = dataset[event_number]
    file.close()

The arr1ev is a NumPy object. There are many methods which allow to manipulate with this object. For example, one can

• print array shape and content:

    print 'arr1ev.shape =', arr1ev.shape
    print 'arr1ev =\n',     arr1ev

Advanced operations

As in previous case we assume thatwhere we assume that all necessary parameters were defined earlier, for example

    hdf5_file_name = '/reg/d/psdm/XPP/xppcom10/hdf5/xppcom10-r0546.h5'
    dataset_name   = '/Configure:0000/Run:0000/CalibCycle:0000/Camera::FrameV1/XppSb4Pim.1:Tm6740.1/image'
    event_number   = 5

The arr1ev is returned as a NumPy object. There are many methods which allow to manipulate with this object. For example, one can

• print array shape and content:

    print 'arr1ev.shape =', arr1ev.shape
    print 'arr1ev =\n',     arr1ev

Advanced operations

As in previous examples we assume that

    file = h5py.File(hdf5_file_name, 'r')
    ds   = file[dataset_name]

Check if the HDF5 item is "File", "Group", or "Data"

isFile    = isinstance(ds,h5py.File)
isGroup   = isinstance(ds,h5py.Group)
isDataset = isinstance(ds,h5py.Dataset)

Get information about HDF5 item

• For all HDF5 items:
  these parameters are available:

  Code Block
  ds.id ds.ref ds.parent ds.file ds.name

h5py.File(hdf5_file_name, 'r')
    ds   = file[dataset_name]

Check if the HDF5 item is "File", "Group", or "Data"

isFile    = isinstance(item, h5py.File)
isGroup   = isinstance(item, h5py.Group)
isDataset = isinstance(item, h5py.Dataset)

This standard Python method returns True or False in each case, respectively.

Get information about HDF5 item

• For all HDF5 items:
  these parameters are available:

  Code Block
  ds.id # for example: <GroupID [1] (U) 33554473> ds.ref # for example: <HDF5 object reference> ds.parent # for example: <HDF5 group "/Configure:0000/Run:0000/CalibCycle:0000" (5 members)> ds.file # for example: <HDF5 file "cxi80410-r0587.h5" (mode r, 3.5G)> ds.name # for example: /Configure:0000/Run:0000/CalibCycle:0000/Camera::FrameV1

• Dataset

  Code Block
  ds.dtype # for example: ('seconds', '<u4'), ('nanoseconds', '<u4')] ds.shape # for example: (1186,) ds.value # for example: (1297610252L, 482193420L)

  Dataset

  Code Block
  dataset_type = ds.dtype dataset_shape = ds.shape dataset_value = ds.value

• Get item attributes for File or Group (if attributes available)

  Code Block
  #group or file dict_attributes = group.attrs attrs_keys = group.attrs.keys() attrs_values = group.attrs.values() number_of_attrs = len(group.attrs) # For example, one of the file attributes is a run number: run_number = file.attrs['runNumber']

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