nexusformat / python-nxs

Python bindings for NAPI
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================ Nexus Python API

Overview

NeXus Python Api binds the NeXus libraries to Python. It brings functionality of the NeXus API to Python for reading, writing and modifying NeXus Files. Python NeXus API imitates the functionality NeXus API though with a more object oriented flavour.

Installation

Requirements


The following software has to be installed on your system in order to 
successfully install and use the Python bindings for NAPI

* Python 2.5 or higher
* ``setuptools`` (replaces the old ``distutils`` code)
* ``sphinx`` to build the documentation
* a working installation of the runtime binaries of ``libNeXus``
* ``numpy``-package

Supported operating systems are: Windows, OS X and Linux.

The bindings should be easily modified for any version of Python which supports 
ctypes and numpy. In order to build the documentation `sphinx` is required.

Building and Installing

This package uses the standard distutils installer for python

.. code-block:: bash

$ python setup.py install

You will also need to make sure that libNeXus can be found.
In order to build the documentation use

.. code-block:: bash

$ python setup.py build_sphinx

To run the tests use

.. code-block:: bash

$ python setup.py test 

Using API from Python

Test Files


The Python NeXus-API includes nxstest.py, which provides similar tests to the
original C api file napi_test.c.

After installing, you can run the test using:

.. code-block:: bash

    $ python [options] [formats]

where options are ``-q`` for quiet and ``-x`` for external, and formats are
``hdf4``, ``hdf5`` and ``xml``.  The default is to test ``hdf5`` format
read/write.

Using The API And An Example

The API's functions aim to reproduce the funtionality of the C API closely. Some low level functionality has been hidden from the user. Memory allocation functions NXmalloc and NXfree are done automatically in the API when needed. The file handle is an object with methods rather than a parameter to functions. Instead of checking status codes, errors raise exceptions.

The input and returned values match the format of the data in the files. On return, python creates values of the correct type. However on input, numeric types must be created correctly using numpy.array(...,dtype='type'). The matching datatypes are:

============== =============== NeXus datatype Python Datatype ============== =============== NX_CHAR char NX_FLOAT32 float32 NX_FLOAT64 float64 NX_UINT8 uint8 NX_INT16 int16 NX_UINT16 uint16 NX_INT32 int32 NX_UINT32 uint32 ============== ===============

Here is simple example program that demonstrates the basic functions and most important differences between the C Nexus Api and the Python Nexus API.

.. code-block:: python

import nxs,numpy

# Access method accepts strings or integer (e.g., nxs.ACC_CREATE5)
f = nxs.open("test.h5", 'w5')
f.makegroup("testgroup", "NXentry")
f.opengroup("testgroup", "NXentry")
f.makegroup("anothergroup", "NXentry")

# Some data to store in the file, this of type int16
data = numpy.array([[0,1,2,3],[4,5,6,7],[8,9,10,11],[12,13,14,15] ],'int16')

# Make a data set for the array. Note that this could also
# be done as f.makedata('data1','int16',[4,4])
f.makedata('data1', dtype=data.dtype, shape=data.shape)
f.opendata("data1")
f.putdata(data)

# Attribute type can be inferred from the data or specified.  If inferred, it
# must match the type of the data.  Attributes are scalars or strings, with
# string length inferred from value.
f.putattr('integer-attribute', 42, 'int16')
f.putattr('double-attribute', 3.14159)
f.closedata() 
# NeXus returns arrays from getattr/getdata/getslab
f.opendata("data1")
print 'data :',f.getdata()

# getnext functions return tuples
attrname,length,type = f.getnextattr ()
value = f.getattr(attrname, length, type)
print 'first attribute: ', value

# ... or you can use iterators for attrs and entries
print 'all attributes'
for attr,value in f.attrs(): 
    print "  %s: %s"%(attr,value)

f.closedata()
f.closegroup()
f.close()

NeXus API Routines



Documentation for the individual methods, and how they differ from the basic
NAPI methods is available from the Python command line.  Rather than duplicate
it here, use the following in Python:

.. code-block:: python

    import nxs
    help(nxs)