python-nxs 4.3.2-svn1919-1 / usr / share / pyshared / nxs / tree.py

#!/usr/bin/env python
# This program is public domain 
# Author: Paul Kienzle, Ray Osborn

"""
NeXus data as Python trees
==========================
The `nexus.tree` modules are designed to accomplish two goals:

    1. To provide convenient access to existing data contained in NeXus files.
    2. To enable new NeXus data to be created and manipulated interactively.

These goals are achieved by mapping hierarchical NeXus data structures directly
into python objects, which either represent NeXus groups or NeXus fields.
Entries in a group are referenced much like fields in a class are referenced in
python. The entire data hierarchy can be referenced at any time, whether the
NeXus data has been loaded in from an existing NeXus file or created dynamically
within the python session. This provides a much more natural scripting interface
to NeXus data than the directory model of the `nexus.napi` interface.

Example 1: Loading a NeXus file
-------------------------------
The following commands loads NeXus data from a file, displays (some of) the
contents as a tree, and then accesses individual data items.

    >>> from nexpy.api import nexus as nx
    >>> a=nx.load('sns/data/ARCS_7326.nxs')
    >>> print a.tree
    root:NXroot
      @HDF5_Version = 1.8.2
      @NeXus_version = 4.2.1
      @file_name = ARCS_7326.nxs
      @file_time = 2010-05-05T01:59:25-05:00
      entry:NXentry
        data:NXdata
          data = float32(631x461x4x825)
            @axes = rotation_angle:tilt_angle:sample_angle:time_of_flight
            @signal = 1
          rotation_angle = float32(632)
            @units = degree
          sample_angle = [ 210.  215.  220.  225.  230.]
            @units = degree
          tilt_angle = float32(462)
            @units = degree
          time_of_flight = float32(826)
            @units = microsecond
        run_number = 7326
        sample:NXsample
          pulse_time = 2854.94747365
            @units = microsecond
    .
    .
    .
    >>> a.entry.run_number
    NXfield(7326)

So the tree returned from load() has an entry for each group, field and
attribute.  You can traverse the hierarchy using the names of the groups.  For
example, tree.entry.instrument.detector.distance is an example of a field
containing the distance to each pixel in the detector. Entries can also be
referenced by NXclass name, such as tree.NXentry[0].instrument. Since there may
be multiple entries of the same NeXus class, the NXclass attribute returns a
(possibly empty) list.

The load() and save() functions are implemented using the class
`nexus.tree.NeXusTree`, a subclass of `nexus.napi.NeXus` which allows all the
usual API functions.

Example 2: Creating a NeXus file dynamically
--------------------------------------------
The second example shows how to create NeXus data dynamically and saves it to a
file. The data are first created as Numpy arrays

    >>> import numpy as np
    >>> x=y=np.linspace(0,2*np.pi,101)
    >>> X,Y=np.meshgrid(y,x)
    >>> z=np.sin(X)*np.sin(Y)

Then a NeXus data groups are created and the data inserted to produce a
NeXus-compliant structure that can be saved to a file.

    >>> root=nx.NXroot(NXentry())
    >>> print root.tree
    root:NXroot
      entry:NXentry
    >>> root.entry.data=nx.NXdata(z,[x,y])

Additional metadata can be inserted before saving the data to a file.

    >>> root.entry.sample=nx.NXsample()
    >>> root.entry.sample.temperature = 40.0
    >>> root.entry.sample.temperature.units = 'K'
    >>> root.save('example.nxs')

NXfield objects have much of the functionality of Numpy arrays. They may be used
in simple arithmetic expressions with other NXfields, Numpy arrays or scalar
values and will be cast as ndarray objects if used as arguments in Numpy
modules.

    >>> x=nx.NXfield(np.linspace(0,10.0,11))
    >>> x
    NXfield([  0.   1.   2. ...,   8.   9.  10.])
    >>> x + 10
    NXfield([ 10.  11.  12. ...,  18.  19.  20.])
    >>> sin(x)
    array([ 0.        ,  0.84147098,  0.90929743, ...,  0.98935825,
        0.41211849, -0.54402111])

If the arithmetic operation is assigned to a NeXus group attribute, it will be
automatically cast as a valid NXfield object with the type and shape determined
by the Numpy array type and shape.

    >>> entry.data.result = sin(x)
    >>> entry.data.result
    NXfield([ 0.          0.84147098  0.90929743 ...,  0.98935825  0.41211849
     -0.54402111])
    >>> entry.data.result.dtype, entry.data.result.shape
    (dtype('float64'), (11,))

NeXus Objects
-------------
Properties of the entry in the tree are referenced by attributes that depend
on the object type, different nx attributes may be available.

Objects (class NXobject) have attributes shared by both groups and fields::
    * nxname   object name
    * nxclass  object class for groups, 'NXfield' for fields
    * nxgroup  group containing the entry, or None for the root
    * attrs    dictionary of NeXus attributes for the object

Groups (class NXgroup) have attributes for accessing children::
    * entries  dictionary of entries within the group
    * component('nxclass')  return group entries of a particular class
    * dir()    print the list of entries in the group
    * tree     return the list of entries and subentries in the group
    * plot()   plot signal and axes for the group, if available

Fields (class NXfield) have attributes for accessing data:
    * shape    dimensions of data in the field
    * dtype    data type
    * nxdata   data in the field

Linked fields or groups (class NXlink) have attributes for accessing the link::
    * nxlink   reference to the linked field or group

NeXus attributes (class NXattr) have a type and a value only::
    * dtype    attribute type
    * nxdata   attribute data

There is a subclass of NXgroup for each group class defined by the NeXus standard,
so it is possible to create an NXgroup of NeXus class NXsample directly using:

    >>> sample = NXsample()

The default group name will be the class name following the 'NX', so the above
group will have an nxname of 'sample'. However, this is overridden by the
attribute name when it is assigned as a group attribute, e.g.,

    >>> entry.sample1 = NXsample()
    >>> entry.sample1.nxname
    sample1

You can traverse the tree by component class instead of component name. Since
there may be multiple components of the same class in one group you will need to
specify which one to use.  For example,

    tree.NXentry[0].NXinstrument[0].NXdetector[0].distance

references the first detector of the first instrument of the first entry.
Unfortunately, there is no guarantee regarding the order of the entries, and it
may vary from call to call, so this is mainly useful in iterative searches.


Unit Conversion
---------------
Data can be stored in the NeXus file in a variety of units, depending on which
facility is storing the file.  This makes life difficult for reduction and
analysis programs which must know the units they are working with.  Our solution
to this problem is to allow the reader to retrieve data from the file in
particular units.  For example, if detector distance is stored in the file using
millimeters you can retrieve them in meters using::

    entry.instrument.detector.distance.convert('m')

See `nexus.unit` for more details on the unit formats supported.

Reading and Writing Slabs
-------------------------
The slab interface to field data works by opening the file handle and keeping it
open as long as the slab interface is needed.  This is done in python 2.5 using
the with statement.  Once the context is entered, get() and put() methods on the
object allow you to read and write data a slab at a time.  For example::

    # Read a Ni x Nj x Nk array one vector at a time
    with root.NXentry[0].data.data as slab:
        Ni,Nj,Nk = slab.shape
        size = [1,1,Nk]
        for i in range(Ni):
            for j in range(Nj):
                value = slab.get([i,j,0],size)

The equivalent can be done in Python 2.4 and lower using the context
functions __enter__ and __exit__::

    slab = data.slab.__enter__()
    ... do the slab functions ...
    data.slab.__exit__()

Plotting NeXus data
-------------------
There is a plot() method for groups that automatically looks for 'signal' and
'axes' attributes within the group in order to determine what to plot. These are
defined by the 'nxsignal' and 'nxaxes' properties of the group. This means that
the method will determine whether the plot should be one- or two- dimensional.
For higher than two dimensions, only the top slice is plotted by default.

The plot method accepts as arguments the standard matplotlib.pyplot.plot format 
strings to customize one-dimensional plots, axis and scale limits, and will
transmit keyword arguments to the matplotlib plotting methods.

    >>> a=nx.load('chopper.nxs')
    >>> a.entry.monitor1.plot()
    >>> a.entry.monitor2.plot('r+', xmax=2600)
    
It is possible to plot over the existing figure with the oplot() method and to
plot with logarithmic intensity scales with the logplot() method. The x- and
y-axes can also be rendered logarithmically using the logx and logy keywards.

Although the plot() method uses matplotlib by default to plot the data, you can replace
this with your own plotter by setting nexus.NXgroup._plotter to your own plotter
class.  The plotter class has one method::

    plot(signal, axes, entry, title, format, **opts)

where signal is the field containing the data, axes are the fields listing the
signal sample points, entry is file/path within the file to the data group and
title is the title of the group or the parent NXentry, if available.
"""
from __future__ import with_statement
from copy import copy, deepcopy

import numpy as np
import napi
from napi import NeXusError

#Memory in MB
NX_MEMORY = 500

__all__ = ['NeXusTree', 'NXobject', 'NXfield', 'NXgroup', 'NXattr',
           'NX_MEMORY', 'setmemory', 'load', 'save', 'tree', 'centers',
           'NXlink', 'NXlinkfield', 'NXlinkgroup', 'SDS', 'NXlinkdata']

#List of defined base classes (later added to __all__)
_nxclasses = ['NXroot', 'NXentry', 'NXsubentry', 'NXdata', 'NXmonitor',
              'NXlog', 'NXsample', 'NXinstrument', 'NXaperture', 'NXattenuator',
              'NXbeam', 'NXbeam_stop', 'NXbending_magnet', 'NXcharacterization',
              'NXcollection', 'NXcollimator', 'NXcrystal', 'NXdetector',
              'NXdisk_chopper', 'NXenvironment', 'NXevent_data',
              'NXfermi_chopper', 'NXfilter', 'NXflipper', 'NXgeometry',
              'NXguide', 'NXinsertion_device', 'NXmirror', 'NXmoderator',
              'NXmonochromator', 'NXnote', 'NXorientation', 'NXparameter',
              'NXpolarizer', 'NXpositioner', 'NXprocess', 'NXsensor', 'NXshape',
              'NXsource', 'NXtranslation', 'NXuser', 'NXvelocity_selector', 'NXtree']

np.set_printoptions(threshold=5)

class NeXusTree(napi.NeXus):

    """
    Structure-based interface to the NeXus file API.

    Usage::

      file = NeXusTree(filename, ['r','rw','w'])
        - open the NeXus file
      root = file.readfile()
        - read the structure of the NeXus file.  This returns a NeXus tree.
      file.writefile(root)
        - write a NeXus tree to the file.
      data = file.readpath(path)
        - read data from a particular path

    Example::

      nx = NeXusTree('REF_L_1346.nxs','r')
      tree = nx.readfile()
      for entry in tree.NXentry:
          process(entry)
      copy = NeXusTree('modified.nxs','w')
      copy.writefile(tree)

    Note that the large datasets are not loaded immediately.  Instead, the
    when the data set is requested, the file is reopened, the data read, and
    the file closed again.  open/close are available for when we want to
    read/write slabs without the overhead of moving the file cursor each time.
    The NXdata objects in the returned tree hold the object values.
    """

    def readfile(self):
        """
        Read the NeXus file structure from the file and return a tree of NXobjects.

        Large datasets are not read until they are needed.
        """
        self.open()
        self.openpath("/")
        root = self._readgroup()
        self.close()
        root._group = None
        # Resolve links (not necessary now that link is set as a property)
        #self._readlinks(root, root)
        root._file = self
        return root

    def writefile(self, tree):
        """
        Write the NeXus file structure to a file.

        The file is assumed to start empty. Updating individual objects can be
        done using the napi interface, with nx.handle as the nexus file handle.
        """
        self.open()
        links = []
        for entry in tree.entries.values():
            links += self._writegroup(entry, path="")
        self._writelinks(links)
        self.close()

    def readpath(self, path):
        """
        Return the data on a particular file path.

        Returns a numpy array containing the data, a python scalar, or a
        string depending on the shape and storage class.
        """
        self.open()
        self.openpath(path)
        try:
            return self.getdata()
        except ValueError:
            return None

    def _readdata(self, name):
        """
        Read a data object and return it as an NXfield or NXlink.
        """
        # Finally some data, but don't read it if it is big
        # Instead record the location, type and size
        self.opendata(name)
        attrs={}
        attrs = self.getattrs()
        if 'target' in attrs and attrs['target'] != self.path:
            # This is a linked dataset; don't try to load it.
            data = NXlinkfield(target=attrs['target'], name=name)
        else:
            dims,type = self.getinfo()
            #Read in the data if it's not too large
            if np.prod(dims) < 1000:# i.e., less than 1k dims
                try:
                    value = self.getdata()
                except ValueError:
                    value = None
            else:
                value = None
            data = NXfield(value=value,name=name,dtype=type,shape=dims,attrs=attrs)
        self.closedata()
        data._infile = data._saved = data._changed = True
        return data

    # These are groups that HDFView explicitly skips
    _skipgroups = ['CDF0.0','_HDF_CHK_TBL_','Attr0.0','RIG0.0','RI0.0',
                   'RIATTR0.0N','RIATTR0.0C']

    def _readchildren(self,n):
        children = {}
        for _item in range(n):
            name,nxclass = self.getnextentry()
            if nxclass in self._skipgroups:
                pass # Skip known bogus classes
            elif nxclass == 'SDS': # NXgetnextentry returns 'SDS' as the class for NXfields
                children[name] = self._readdata(name)
            else:
                self.opengroup(name,nxclass)
                children[name] = self._readgroup()
                self.closegroup()
        return children

    def _readgroup(self):
        """
        Read the currently open group and return it as an NXgroup.
        """
        n,name,nxclass = self.getgroupinfo()
        attrs = {}
        attrs = self.getattrs()
        if 'target' in attrs and attrs['target'] != self.path:
            # This is a linked group; don't try to load it.
            group = NXlinkgroup(target=attrs['target'], name=name)
        else:
            children = self._readchildren(n)
            # If we are subclassed with a handler for the particular
            # NXentry class name use that constructor for the group
            # rather than the generic NXgroup class.
            group = NXgroup(nxclass=nxclass,name=name,attrs=attrs,entries=children)
            # Build chain back structure
            for obj in children.values():
                obj._group = group
        group._infile = group._saved = group._changed = True
        return group

    def _readlinks(self, root, group):
        """
        Convert linked objects into direct references.
        """
        for entry in group.entries.values():
            if isinstance(entry, NXlink):
                link = root
                try:
                    for level in entry._target[1:].split('/'):
                        link = getattr(link,level)
                    entry.nxlink = link
                except AttributeError:
                    pass
            elif isinstance(entry, NXgroup):
                self._readlinks(root, entry)

    def _writeattrs(self, attrs):
        """
        Return the attributes for the currently open group/data.

        If no group or data object is open, the file attributes are returned.
        """
        for name,pair in attrs.iteritems():
            self.putattr(name,pair.nxdata,pair.dtype)

    def _writedata(self, data, path):
        """
        Write the given data to a file.

        NXlinks cannot be written until the linked group is created, so
        this routine returns the set of links that need to be written.
        Call writelinks on the list.
        """

        path = path + "/" + data.nxname

        # If the data is linked then
        if hasattr(data,'_target'):
            return [(path, data._target)]

        shape = data.shape
        if shape == (): shape = (1,)

        #If the array size is too large, their product needs a long integer
        if np.prod(shape) > 10000:
            # Compress the fastest moving dimension of large datasets
            slab_dims = np.ones(len(shape),'i')
            if shape[-1] < 100000:
                slab_dims[-1] = shape[-1]
            else:
                slab_dims[-1] = 100000
            self.compmakedata(data.nxname, data.dtype, shape, 'lzw', slab_dims)
        else:
            # Don't use compression for small datasets
            try:
                self.makedata(data.nxname, data.dtype, shape)
            except StandardError,errortype:
                print "Error in tree, makedata: ",errortype

        self.opendata(data.nxname)
        self._writeattrs(data.attrs)
        value = data.nxdata
        if value is not None:
            self.putdata(data.nxdata)
        self.closedata()
        return []

    def _writegroup(self, group, path):
        """
        Write the given group structure, including the data.

        NXlinks cannot be written until the linked group is created, so
        this routine returns the set of links that need to be written.
        Call writelinks on the list.
        """
        path = path + "/" + group.nxname

        links = []
        self.makegroup(group.nxname, group.nxclass)
        self.opengroup(group.nxname, group.nxclass)
        self._writeattrs(group.attrs)
        if hasattr(group, '_target'):
            links += [(path, group._target)]
        for child in group.entries.values():
            if child.nxclass == 'NXfield':
                links += self._writedata(child,path)
            elif hasattr(child,'_target'):
                links += [(path+"/"+child.nxname,child._target)]
            else:
                links += self._writegroup(child,path)
        self.closegroup()
        return links

    def _writelinks(self, links):
        """
        Create links within the NeXus file.

        THese are defined by the set of pairs returned by _writegroup.
        """
        gid = {}

        # identify targets
        for path,target in links:
            gid[target] = None

        # find gids for targets
        for target in gid.iterkeys():
            self.openpath(target)
            # Can't tell from the name if we are linking to a group or
            # to a dataset, so cheat and rely on getdataID to signal
            # an error if we are not within a group.
            try:
                gid[target] = self.getdataID()
            except NeXusError:
                gid[target] = self.getgroupID()

        # link sources to targets
        for path,target in links:
            if path != target:
                # ignore self-links
                parent = "/".join(path.split("/")[:-1])
                self.openpath(parent)
                self.makelink(gid[target])


def _readaxes(axes):
    """
    Return a list of axis names stored in the 'axes' attribute.

    The delimiter separating each axis can be white space, a comma, or a colon.
    """
    import re
    sep=re.compile('[\[]*(\s*,*:*)+[\]]*')
    return filter(lambda x: len(x)>0, sep.split(axes))


class AttrDict(dict):

    """
    A dictionary class to assign all attributes to the NXattr class.
    """

    def __setitem__(self, key, value):
        if isinstance(value, NXattr):
            dict.__setitem__(self, key, value)
        else:
            dict.__setitem__(self, key, NXattr(value))


class NXattr(object):

    """
    Class for NeXus attributes of a NXfield or NXgroup object.

    This class is only used for NeXus attributes that are stored in a
    NeXus file and helps to distinguish them from Python attributes.
    There are two Python attributes for each NeXus attribute.

    Python Attributes
    -----------------
    nxdata : string, Numpy scalar, or Numpy ndarray
        The value of the NeXus attribute.
    dtype : string
        The data type of the NeXus attribute. This is set to 'char' for
        a string attribute or the string of the corresponding Numpy data type
        for a numeric attribute.

    NeXus Attributes
    ----------------
    NeXus attributes are stored in the 'attrs' dictionary of the parent object,
    NXfield or NXgroup, but can often be referenced or assigned using the
    attribute name as if it were an object attribute.

    For example, after assigning the NXfield, the following three attribute
    assignments are all equivalent::

        >>> entry.sample.temperature = NXfield(40.0)
        >>> entry.sample.temperature.attrs['units'] = 'K'
        >>> entry.sample.temperature.units = NXattr('K')
        >>> entry.sample.temperature.units = 'K'

    The third version above is only allowed for NXfield attributes and is
    not allowed if the attribute has the same name as one of the following
    internally defined attributes, i.e.,

    ['entries', 'attrs', 'dtype','shape']

    or if the attribute name begins with 'nx' or '_'. It is only possible to
    reference attributes with one of the proscribed names using the 'attrs'
    dictionary.

    """

    def __init__(self,value=None,dtype=''):
        if isinstance(value, NXattr):
            self._data,self._dtype = value.nxdata,value.dtype
        elif dtype:
            if dtype in np.typeDict:
                self._data,self._dtype = np.__dict__[dtype](value),dtype
            elif dtype == 'char':
                self._data,self._dtype = str(value),dtype
            else:
                raise NeXusError("Invalid data type")
        else:
            if isinstance(value, str):
                self._data,self._dtype = str(value), 'char'
            elif value is not None:
                if isinstance(value, NXobject):
                    raise NeXusError("A data attribute cannot be a NXfield or NXgroup")
                else:
                    self._data = np.array(value)
                self._dtype = self._data.dtype.name
                if self._data.size == 1:
                    self._data = np.__dict__[self._dtype](self._data)
            else:
                self._data,self._dtype = None, 'char'

    def __str__(self):
        return str(self.nxdata)

    def __repr__(self):
        if str(self.dtype) == 'char':
            return "NXattr('%s')"%self.nxdata
        else:
            return "NXattr(%s)"%self.nxdata

    def __eq__(self, other):
        """
        Return true if the value of the attribute is the same as the other.
        """
        if isinstance(other, NXattr):
            return self.nxdata == other.nxdata
        else:
            return self.nxdata == other

    def _getdata(self):
        """
        Return the attribute value.
        """
        return self._data

    def _getdtype(self):
        return self._dtype

    nxdata = property(_getdata,doc="The attribute values")
    dtype = property(_getdtype, "Data type of NeXus attribute")

_npattrs = filter(lambda x: not x.startswith('_'), np.ndarray.__dict__.keys())

class NXobject(object):

    """
    Abstract base class for elements in NeXus files.

    The object has a subclass of NXfield, NXgroup, or one of the NXgroup
    subclasses. Child nodes should be accessible directly as object attributes.
    Constructors for NXobject objects are defined by either the NXfield or
    NXgroup classes.

    Python Attributes
    -----------------
    nxclass : string
        The class of the NXobject. NXobjects can have class NXfield, NXgroup, or
        be one of the NXgroup subclasses.
    nxname : string
        The name of the NXobject. Since it is possible to reference the same
        Python object multiple times, this is not necessarily the same as the
        object name. However, if the object is part of a NeXus tree, this will
        be the attribute name within the tree.
    nxgroup : NXgroup
        The parent group containing this object within a NeXus tree. If the
        object is not part of any NeXus tree, it will be set to None.
    nxpath : string
        The path to this object with respect to the root of the NeXus tree. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.
    nxroot : NXgroup
        The root object of the NeXus tree containing this object. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.
    nxfile : NeXusTree
        The file handle of the root object of the NeXus tree containing this
        object.
    filename : string
        The file name of NeXus object's tree file handle.
    attrs : dict
        A dictionary of the NeXus object's attributes.

    Methods
    -------
    dir(self, attrs=False, recursive=False):
        Print the group directory.

        The directory is a list of NeXus objects within this group, either NeXus
        groups or NXfield data. If 'attrs' is True, NXfield attributes are
        displayed. If 'recursive' is True, the contents of child groups are also
        displayed.

    tree:
        Return the object's tree as a string.

        It invokes the 'dir' method with both 'attrs' and 'recursive'
        set to True. Note that this is defined as a property attribute and
        does not require parentheses.

    save(self, filename, format='w5')
        Save the NeXus group into a file

        The object is wrapped in an NXroot group (with name 'root') and an
        NXentry group (with name 'entry'), if necessary, in order to produce
        a valid NeXus file.

    """

    _class = "unknown"
    _name = "unknown"
    _group = None
    _file = None
    _infile = False
    _saved = False
    _changed = True

    def __str__(self):
        return "%s:%s"%(self.nxclass,self.nxname)

    def __repr__(self):
        return "NXobject('%s','%s')"%(self.nxclass,self.nxname)

    def _setattrs(self, attrs):
        for k,v in attrs.items():
            self._attrs[k] = v

    def _str_name(self,indent=0):
        if self.nxclass == 'NXfield':
            return " "*indent+self.nxname
        else:
            return " "*indent+self.nxname+':'+self.nxclass

    def _str_value(self,indent=0):
        return ""

    def _str_attrs(self,indent=0):
        names = self.attrs.keys()
        names.sort()
        result = []
        for k in names:
            result.append(" "*indent+"@%s = %s"%(k,self.attrs[k].nxdata))
        return "\n".join(result)

    def _str_tree(self,indent=0,attrs=False,recursive=False):
        """
        Print current object and possibly children.
        """
        result = [self._str_name(indent=indent)]
        if attrs and self.attrs:
            result.append(self._str_attrs(indent=indent+2))
        # Print children
        entries = self.entries
        if entries:
            names = entries.keys()
            names.sort()
            if recursive:
                for k in names:
                    result.append(entries[k]._str_tree(indent=indent+2,
                                                       attrs=attrs, recursive=True))
            else:
                for k in names:
                    result.append(entries[k]._str_name(indent=indent+2))
        result
        return "\n".join(result)

    def walk(self):
        if False: yield

    def dir(self,attrs=False,recursive=False):
        """
        Print the object directory.

        The directory is a list of NeXus objects within this object, either
        NeXus groups or NXfields. If 'attrs' is True, NXfield attributes are
        displayed. If 'recursive' is True, the contents of child groups are
        also displayed.
        """
        print self._str_tree(attrs=attrs,recursive=recursive)

    @property
    def tree(self):
        """
        Return the directory tree as a string.

        The tree contains all child objects of this object and their children.
        It invokes the 'dir' method with both 'attrs' and 'recursive' set
        to True.
        """
        return self._str_tree(attrs=True,recursive=True)

    def __enter__(self):
        """
        Open the datapath for reading or writing.

        Note: the results are undefined if you try accessing
        more than one slab at a time.  Don't nest your
        "with data" statements!
        """
        self._close_on_exit = not self.nxfile.isopen
        self.nxfile.open() # Force file open even if closed
        self.nxfile.openpath(self.nxpath)
        self._incontext = True
        return self.nxfile

    def __exit__(self, type, value, traceback):
        """
        Close the file associated with the data.
        """
        self._incontext = False
        if self._close_on_exit:
            self.nxfile.close()

    def save(self, filename=None, format='w5'):
        """
        Save the NeXus object to a data file.

        An error is raised if the object is an NXroot group from an external file
        that has been opened as readonly and no file name is specified.

        The object is wrapped in an NXroot group (with name 'root') and an
        NXentry group (with name 'entry'), if necessary, in order to produce
        a valid NeXus file.
        
        Example
        -------
        >>> data = NXdata(sin(x), x)
        >>> data.save('file.nxs')
        >>> print data.nxroot.tree
        root:NXroot
          @HDF5_Version = 1.8.2
          @NeXus_version = 4.2.1
          @file_name = file.nxs
          @file_time = 2012-01-20T13:14:49-06:00
          entry:NXentry
            data:NXdata
              axis1 = float64(101)
              signal = float64(101)
                @axes = axis1
                @signal = 1              
        >>> root.entry.data.axis1.units = 'meV'
        >>> root.save()
        """
        if filename:
            if self.nxclass == "NXroot":
                root = self
            elif self.nxclass == "NXentry":
                root = NXroot(self)
            else:
                root = NXroot(NXentry(self))
            if root.nxfile: root.nxfile.close()
            file = NeXusTree(filename, format)
            file.writefile(root)
            file.close()
            root._file = NeXusTree(filename, 'rw')
            root._setattrs(root._file.getattrs())
            for node in root.walk():
                node._infile = node._saved = True
            
        elif self.nxfile:
            for entry in self.nxroot.values():
                entry.write()

        else:
            raise NeXusError("No output file specified")

    @property
    def infile(self):
        """
        Returns True if the object has been created in a NeXus file.
        """
        return self._infile
    
    @property
    def saved(self):
        """
        Returns True if the object has been saved to a file.
        """
        return self._saved

    @property
    def changed(self):
        """
        Returns True if the object has been changed.
        
        This property is for use by external scripts that need to track
        which NeXus objects have been changed.
        """
        return self._changed
    
    def set_unchanged(self, recursive=False):
        """
        Set an object's change status to unchanged.
        """
        if recursive:
            for node in self.walk():
                node._changed = False
        else:
            self._changed = False
    
    def _getclass(self):
        return self._class

    def _getname(self):
        return self._name

    def _setname(self, value):
        self._name = str(value)

    def _getgroup(self):
        return self._group

    def _getpath(self):
        if self.nxgroup is None:
            return ""
        elif isinstance(self.nxgroup, NXroot):
            return "/" + self.nxname
        else:
            return self.nxgroup._getpath()+"/"+self.nxname

    def _getroot(self):
        if self.nxgroup is None:
            return self
        elif isinstance(self.nxgroup, NXroot):
            return self.nxgroup
        else:
            return self.nxgroup._getroot()

    def _getfile(self):
        return self.nxroot._file

    def _getfilename(self):
        return self.nxroot._file.filename

    def _getattrs(self):
        return self._attrs

    nxclass = property(_getclass, doc="Class of NeXus object")
    nxname = property(_getname, _setname, doc="Name of NeXus object")
    nxgroup = property(_getgroup, doc="Parent group of NeXus object")
    nxpath = property(_getpath, doc="Path to NeXus object")
    nxroot = property(_getroot, doc="Root group of NeXus object's tree")
    nxfile = property(_getfile, doc="File handle of NeXus object's tree")
    attrs = property(_getattrs, doc="NeXus attributes for an object")


class NXfield(NXobject):

    """
    A NeXus data field.

    This is a subclass of NXobject that contains scalar, array, or string data
    and associated NeXus attributes.

    NXfield(value=None, name='unknown', dtype='', shape=[], attrs={}, file=None,
            path=None, group=None, **attr)

    Input Parameters
    ----------------
    value : scalar value, Numpy array, or string
        The numerical or string value of the NXfield, which is directly
        accessible as the NXfield attribute 'nxdata'.
    name : string
        The name of the NXfield, which is directly accessible as the NXfield
        attribute 'name'. If the NXfield is initialized as the attribute of a
        parent object, the name is automatically set to the name of this
        attribute.
    dtype : string
        The data type of the NXfield value, which is directly accessible as the
        NXfield attribute 'dtype'. Valid input types correspond to standard
        Numpy data types, using names defined by the NeXus API,
        i.e., 'float32' 'float64'
              'int8' 'int16' 'int32' 'int64'
              'uint8' 'uint16' 'uint32' 'uint64'
              'char'
        If the data type is not specified, then it is determined automatically
        by the data type of the 'value' parameter.
    shape : list of ints
        The dimensions of the NXfield data, which is accessible as the NXfield
        attribute 'shape'. This corresponds to the shape of the Numpy array.
        Scalars (numeric or string) are stored as Numpy zero-rank arrays,
        for which shape=[].
    attrs : dict
        A dictionary containing NXfield attributes. The dictionary values should
        all have class NXattr.
    file : filename
        The file from which the NXfield has been read.
    path : string
        The path to this object with respect to the root of the NeXus tree,
        using the convention for unix file paths.
    group : NXgroup or subclass of NXgroup
        The parent NeXus object. If the NXfield is initialized as the attribute
        of a parent group, this attribute is automatically set to the parent group.

    Python Attributes
    -----------------
    nxclass : 'NXfield'
        The class of the NXobject.
    nxname : string
        The name of the NXfield. Since it is possible to reference the same
        Python object multiple times, this is not necessarily the same as the
        object name. However, if the field is part of a NeXus tree, this will
        be the attribute name within the tree.
    nxgroup : NXgroup
        The parent group containing this field within a NeXus tree. If the
        field is not part of any NeXus tree, it will be set to None.
    dtype : string or Numpy dtype
        The data type of the NXfield value. If the NXfield has been initialized
        but the data values have not been read in or defined, this is a string.
        Otherwise, it is set to the equivalent Numpy dtype.
    shape : list or tuple of ints
        The dimensions of the NXfield data. If the NXfield has been initialized
        but the data values have not been read in or defined, this is a list of
        ints. Otherwise, it is set to the equivalent Numpy shape, which is a
        tuple. Scalars (numeric or string) are stored as Numpy zero-rank arrays,
        for which shape=().
    attrs : dict
        A dictionary of all the NeXus attributes associated with the field.
        These are objects with class NXattr.
    nxdata : scalar, Numpy array or string
        The data value of the NXfield. This is normally initialized using the
        'value' parameter (see above). If the NeXus data is contained
        in a file and the size of the NXfield array is too large to be stored
        in memory, the value is not read in until this attribute is directly
        accessed. Even then, if there is insufficient memory, a value of None
        will be returned. In this case, the NXfield array should be read as a
        series of smaller slabs using 'get'.
    nxdata_as('units') : scalar value or Numpy array
        If the NXfield 'units' attribute has been set, the data values, stored
        in 'nxdata', are returned after conversion to the specified units.
    nxpath : string
        The path to this object with respect to the root of the NeXus tree. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.
    nxroot : NXgroup
        The root object of the NeXus tree containing this object. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.

    NeXus Attributes
    ----------------
    NeXus attributes are stored in the 'attrs' dictionary of the NXfield, but
    can usually be assigned or referenced as if they are Python attributes, as
    long as the attribute name is not the same as one of those listed above.
    This is to simplify typing in an interactive session and should not cause
    any problems because there is no name clash with attributes so far defined
    within the NeXus standard. When writing modules, it is recommended that the
    attributes always be referenced using the 'attrs' dictionary if there is
    any doubt.

    a) Assigning a NeXus attribute

    In the example below, after assigning the NXfield, the following three
    NeXus attribute assignments are all equivalent:

        >>> entry.sample.temperature = NXfield(40.0)
        >>> entry.sample.temperature.attrs['units'] = 'K'
        >>> entry.sample.temperature.units = NXattr('K')
        >>> entry.sample.temperature.units = 'K'

    b) Referencing a NeXus attribute

    If the name of the NeXus attribute is not the same as any of the Python
    attributes listed above, or one of the methods listed below, or any of the
    attributes defined for Numpy arrays, they can be referenced as if they were
    a Python attribute of the NXfield. However, it is only possible to reference
    attributes with one of the proscribed names using the 'attrs' dictionary.

        >>> entry.sample.temperature.tree = 10.0
        >>> entry.sample.temperature.tree
        temperature = 40.0
          @tree = 10.0
          @units = K
        >>> entry.sample.temperature.attrs['tree']
        NXattr(10.0)

    Numerical Operations on NXfields
    --------------------------------
    NXfields usually consist of arrays of numeric data with associated
    meta-data, the NeXus attributes. The exception is when they contain
    character strings. This makes them similar to Numpy arrays, and this module
    allows the use of NXfields in numerical operations in the same way as Numpy
    ndarrays. NXfields are technically not a sub-class of the ndarray class, but
    most Numpy operations work on NXfields, returning either another NXfield or,
    in some cases, an ndarray that can easily be converted to an NXfield.

        >>> x = NXfield((1.0,2.0,3.0,4.0))
        >>> print x+1
        [ 2.  3.  4.  5.]
        >>> print 2*x
        [ 2.  4.  6.  8.]
        >>> print x/2
        [ 0.5  1.   1.5  2. ]
        >>> print x**2
        [  1.   4.   9.  16.]
        >>> print x.reshape((2,2))
        [[ 1.  2.]
         [ 3.  4.]]
        >>> y = NXfield((0.5,1.5,2.5,3.5))
        >>> x+y
        NXfield(name=x,value=[ 1.5  3.5  5.5  7.5])
        >>> x*y
        NXfield(name=x,value=[  0.5   3.    7.5  14. ])
        >>> (x+y).shape
        (4,)
        >>> (x+y).dtype
        dtype('float64')

    All these operations return valid NXfield objects containing the same
    attributes as the first NXobject in the expression. The 'reshape' and
    'transpose' methods also return NXfield objects.

    It is possible to use the standard slice syntax.

        >>> x=NXfield(np.linspace(0,10,11))
        >>> x
        NXfield([  0.   1.   2. ...,   8.   9.  10.])
        >>> x[2:5]
        NXfield([ 2.  3.  4.])

    In addition, it is possible to use floating point numbers as the slice
    indices. If one of the indices is not integer, both indices are used to
    extract elements in the array with values between the two index values.

        >>> x=NXfield(np.linspace(0,100.,11))
        >>> x
        NXfield([   0.   10.   20. ...,   80.   90.  100.])
        >>> x[20.:50.]
        NXfield([ 20.  30.  40.  50.])

    The standard Numpy ndarray attributes and methods will also work with
    NXfields, but will return scalars or Numpy arrays.

        >>> x.size
        4
        >>> x.sum()
        10.0
        >>> x.max()
        4.0
        >>> x.mean()
        2.5
        >>> x.var()
        1.25
        >>> x.reshape((2,2)).sum(1)
        array([ 3.,  7.])

    Finally, NXfields are cast as ndarrays for operations that require them.
    The returned value will be the same as for the equivalent ndarray
    operation, e.g.,

    >>> np.sin(x)
    array([ 0.84147098,  0.90929743,  0.14112001, -0.7568025 ])
    >>> np.sqrt(x)
    array([ 1.        ,  1.41421356,  1.73205081,  2.        ])

    Methods
    -------
    dir(self, attrs=False):
        Print the NXfield specification.

        This outputs the name, dimensions and data type of the NXfield.
        If 'attrs' is True, NXfield attributes are displayed.

    tree:
        Return the NXfield's tree.

        It invokes the 'dir' method with both 'attrs' and 'recursive'
        set to True. Note that this is defined as a property attribute and
        does not require parentheses.


    save(self, filename, format='w5')
        Save the NXfield into a file wrapped in a NXroot group and NXentry group
        with default names. This is equivalent to

        >>> NXroot(NXentry(NXfield(...))).save(filename)

    Examples
    --------
    >>> x = NXfield(np.linspace(0,2*np.pi,101), units='degree')
    >>> phi = x.nxdata_as(units='radian')
    >>> y = NXfield(np.sin(phi))

    # Read a Ni x Nj x Nk array one vector at a time
    >>> with root.NXentry[0].data.data as slab:
            Ni,Nj,Nk = slab.shape
            size = [1,1,Nk]
            for i in range(Ni):
                for j in range(Nj):
                    value = slab.get([i,j,0],size)

    """

    def __init__(self, value=None, name='field', dtype=None, shape=(), group=None,
                 attrs={}, **attr):
        if isinstance(value, list) or isinstance(value, tuple):
            value = np.array(value)
        self._value = value
        self._class = 'NXfield'
        self._name = name.replace(' ','_')
        self._group = group
        self._dtype = dtype
        if dtype == 'char':
            self._dtype = 'char'
        elif dtype in np.typeDict:
            self._dtype = np.dtype(dtype)
        elif dtype:
            raise NeXusError("Invalid data type: %s" % dtype)
        self._shape = tuple(shape)
        # Append extra keywords to the attribute list
        self._attrs = AttrDict()
        for key in attr.keys():
            attrs[key] = attr[key]
        # Convert NeXus attributes to python attributes
        self._setattrs(attrs)
        if 'units' in attrs:
            units = attrs['units']
        else:
            units = None
        self._incontext = False
        del attrs
        if value is not None and dtype == 'char': value = str(value)
        self._setdata(value)
        self._saved = False
        self._changed = True

    def __repr__(self):
        if self._value is not None:
            if str(self.dtype) == 'char':
                return "NXfield('%s')" % str(self)
            else:
                return "NXfield(%s)" % self._str_value()
        else:
            return "NXfield(dtype=%s,shape=%s)" % (self.dtype,self.shape)

    def __getattr__(self, name):
        """
        Enable standard numpy ndarray attributes if not otherwise defined.
        """
        if name in _npattrs:
            return self.nxdata.__getattribute__(name)
        elif name in self.attrs:
            return self.attrs[name].nxdata
        raise KeyError(name+" not in "+self.nxname)

    def __setattr__(self, name, value):
        """
        Add an attribute to the NXfield 'attrs' dictionary unless the attribute
        name starts with 'nx' or '_', or unless it is one of the standard Python
        attributes for the NXfield class.
        """
        if name.startswith('_') or name.startswith('nx'):
            object.__setattr__(self, name, value)
        elif isinstance(value, NXattr):
            self._attrs[name] = value
            self._saved = False
            self._changed = True
        else:
            self._attrs[name] = NXattr(value)
            self._saved = False
            self._changed = True

    def __getitem__(self, index):
        """
        Returns a slice from the NXfield.

        In most cases, the slice values are applied to the NXfield nxdata array
        and returned within an NXfield object with the same metadata. However,
        if the array is one-dimensional and the index start and stop values
        are real, the nxdata array is returned with values between those limits.
        This is to allow axis arrays to be limited by their actual value. This
        real-space slicing should only be used on monotonically increasing (or
        decreasing) one-dimensional arrays.
        """
        if isinstance(index, slice) and \
           (isinstance(index.start, float) or isinstance(index.stop, float)):
            index = slice(self.index(index.start), self.index(index.stop,max=True)+1)
        if self._value is not None:
            result = self.nxdata.__getitem__(index)
        else:
            offset = np.zeros(len(self.shape),dtype=int)
            size = np.array(self.shape)
            if isinstance(index, int):
                offset[0] = index
                size[0] = 1
            else:
                if isinstance(index, slice): index = [index]
                i = 0
                for ind in index:
                    if isinstance(ind, int):
                        offset[i] = ind
                        size[i] = 1
                    else:
                        if ind.start: offset[i] = ind.start
                        if ind.stop: size[i] = ind.stop - offset[i]
                    i = i + 1
            try:
                result = self.get(offset, size)
            except ValueError:
                result = self.nxdata.__getitem__(index)
        return NXfield(result, name=self.nxname, attrs=self.attrs)

    def __setitem__(self, index, value):
        """
        Assign a slice to the NXfield.
        """
        if self._value is not None:
            self.nxdata[index] = value
            self._saved = False
            self._changed = True
        else:
            raise NeXusError("NXfield dataspace not yet allocated")

    def __deepcopy__(self, memo):
        dpcpy = self.__class__()
        memo[id(self)] = dpcpy
        dpcpy._value = copy(self._value)
        dpcpy._name = copy(self.nxname)
        dpcpy._dtype = copy(self.dtype)
        dpcpy._shape = copy(self.shape)
        for k, v in self.attrs.items():
            dpcpy.attrs[k] = copy(v)
        return dpcpy

    def __len__(self):
        """
        Return the length of the NXfield data.
        """
        return np.prod(self.shape)

    def index(self, value, max=False):
        """
        Return the index of the NXfield nxdata array that is greater than or equal to the value.

        If max, then return the index that is less than or equal to the value.
        This should only be used on one-dimensional monotonically increasing arrays.
        """
        if max:
            return len(self.nxdata)-len(self.nxdata[self.nxdata>=value])
        else:
            return len(self.nxdata[self.nxdata<value])

    def __array__(self):
        """
        Cast the NXfield as an array when it is expected by numpy
        """
        return self.nxdata

    def __eq__(self, other):
        """
        Return true if the values of the NXfield are the same.
        """
        if isinstance(other, NXfield):
            if isinstance(self.nxdata, np.ndarray) and isinstance(other.nxdata, np.ndarray):
                return all(self.nxdata == other.nxdata)
            else:
                return self.nxdata == other.nxdata
        else:
            return False

    def __ne__(self, other):
        """
        Return true if the values of the NXfield are not the same.
        """
        if isinstance(other, NXfield):
            if isinstance(self.nxdata, np.ndarray) and isinstance(other.nxdata, np.ndarray):
                return any(self.nxdata != other.nxdata)
            else:
                return self.nxdata != other.nxdata
        else:
            return True

    def __add__(self, other):
        """
        Return the sum of the NXfield and another NXfield or number.
        """
        if isinstance(other, NXfield):
            return NXfield(value=self.nxdata+other.nxdata, name=self.nxname,
                           attrs=self.attrs)
        else:
            return NXfield(value=self.nxdata+other, name=self.nxname,
                           attrs=self.attrs)

    def __radd__(self, other):
        """
        Return the sum of the NXfield and another NXfield or number.

        This variant makes __add__ commutative.
        """
        return self.__add__(other)

    def __sub__(self, other):
        """
        Return the NXfield with the subtraction of another NXfield or number.
        """
        if isinstance(other, NXfield):
            return NXfield(value=self.nxdata-other.nxdata, name=self.nxname,
                           attrs=self.attrs)
        else:
            return NXfield(value=self.nxdata-other, name=self.nxname,
                           attrs=self.attrs)

    def __mul__(self, other):
        """
        Return the product of the NXfield and another NXfield or number.
        """
        if isinstance(other, NXfield):
            return NXfield(value=self.nxdata*other.nxdata, name=self.nxname,
                           attrs=self.attrs)
        else:
            return NXfield(value=self.nxdata*other, name=self.nxname,
                          attrs=self.attrs)

    def __rmul__(self, other):
        """
        Return the product of the NXfield and another NXfield or number.

        This variant makes __mul__ commutative.
        """
        return self.__mul__(other)

    def __div__(self, other):
        """
        Return the NXfield divided by another NXfield or number.
        """
        if isinstance(other, NXfield):
            return NXfield(value=self.nxdata/other.nxdata, name=self.nxname,
                           attrs=self.attrs)
        else:
            return NXfield(value=self.nxdata/other, name=self.nxname,
                           attrs=self.attrs)

    def __rdiv__(self, other):
        """
        Return the inverse of the NXfield divided by another NXfield or number.
        """
        if isinstance(other, NXfield):
            return NXfield(value=other.nxdata/self.nxdata, name=self.nxname,
                           attrs=self.attrs)
        else:
            return NXfield(value=other/self.nxdata, name=self.nxname,
                           attrs=self.attrs)

    def __pow__(self, power):
        """
        Return the NXfield raised to the specified power.
        """
        return NXfield(value=pow(self.nxdata,power), name=self.nxname,
                       attrs=self.attrs)

    def reshape(self, shape):
        """
        Returns an NXfield with the specified shape.
        """
        return NXfield(value=self.nxdata.reshape(shape), name=self.nxname,
                       attrs=self.attrs)

    def transpose(self):
        """
        Returns an NXfield containing the transpose of the data array.
        """
        return NXfield(value=self.nxdata.transpose(), name=self.nxname,
                       attrs=self.attrs)

    @property
    def T(self):
        return self.transpose()

    def centers(self):
        """
        Returns an NXfield with the centers of a single axis
        assuming it contains bin boundaries.
        """
        return NXfield((self.nxdata[:-1]+self.nxdata[1:])/2,
                        name=self.nxname,attrs=self.attrs)

    def read(self):
        """
        Read the NXfield, including attributes, from the NeXus file.

        The data values are read provided they do not exceed NX_MEMORY. In that
        case, the data have to be read in as slabs using the get method.
        """
        if self.nxfile:
            with self as path:
                self._setattrs(path.getattrs())
                shape, dtype = path.getinfo()
                if dtype == 'char':
                    self._value = path.getdata()
                elif np.prod(shape) * np.dtype(dtype).itemsize <= NX_MEMORY*1024*1024:
                    self._value = path.getdata()
                else:
                    raise MemoryError('Data size larger than NX_MEMORY=%s MB' % NX_MEMORY)
                self._shape = tuple(shape)
                self._dtype = dtype
                if dtype == 'char':
                    self._dtype = 'char'
                elif dtype in np.typeDict:
                    self._dtype = np.dtype(dtype)
                self._infile = self._saved = self._changed = True
        else:
            raise IOError("Data is not attached to a file")

    def write(self):
        """
        Write the NXfield, including attributes, to the NeXus file.
        """
        if self.nxfile:
            if self.nxfile.mode == napi.ACC_READ:
                raise NeXusError("NeXus file is readonly")
            if not self.infile:
                shape = self.shape
                if shape == (): shape = (1,)
                with self.nxgroup as path:
                    if np.prod(shape) > 10000:
                    # Compress the fastest moving dimension of large datasets
                        slab_dims = np.ones(len(shape),'i')
                        if shape[-1] < 100000:
                            slab_dims[-1] = shape[-1]
                        else:
                            slab_dims[-1] = 100000
                        path.compmakedata(self.nxname, self.dtype, shape, 'lzw', 
                                          slab_dims)
                    else:
                    # Don't use compression for small datasets
                        path.makedata(self.nxname, self.dtype, shape)
                self._infile = True
            if not self.saved:            
                with self as path:
                    path._writeattrs(self.attrs)
                    value = self.nxdata
                    if value is not None:
                        path.putdata(value)
                self._saved = True
        else:
            raise IOError("Data is not attached to a file")

    def get(self, offset, size):
        """
        Return a slab from the data array.

        Offsets are 0-origin. Shape can be inferred from the data.
        Offset and shape must each have one entry per dimension.

        Corresponds to NXgetslab(handle,data,offset,shape)
        """
        if self.nxfile:
            with self as path:
                value = path.getslab(offset,size)
                return value
        else:
            raise IOError("Data is not attached to a file")

    def put(self, data, offset, refresh=True):
        """
        Put a slab into the data array.

        Offsets are 0-origin.  Shape can be inferred from the data.
        Offset and shape must each have one entry per dimension.

        Corresponds to NXputslab(handle,data,offset,shape)
        """
        if self.nxfile:
            if self.nxfile.mode == napi.ACC_READ:
                raise NeXusError("NeXus file is readonly")
            with self as path:
                if isinstance(data, NXfield):
                    path.putslab(data.nxdata.astype(self.dtype), offset, data.shape)
                else:
                    data = np.array(data)
                    path.putslab(data.astype(self.dtype), offset, data.shape)
            if refresh: self.read()
        else:
            raise IOError("Data is not attached to a file")

    def add(self, data, offset, refresh=True):
        """
        Add a slab into the data array.

        Calls get to read in existing data before adding the value
        and calling put. It assumes that the two sets of data have
        compatible data types.
        """
        if isinstance(data, NXfield):
            value = self.get(offset, data.shape)
            self.put(data.nxdata.astype(self.dtype)+value, offset)
        else:
            value = self.get(offset, data.shape)
            self.put(data.astype(self.dtype)+value, offset)
        if refresh: self.refresh()

    def refresh(self):
        """
        Rereads the data from the file.

        If put has been called, then nxdata is no longer synchronized with the
        file making a refresh necessary. This will only be performed if nxdata
        already stores the data.
        """
        if self._value is not None:
            if self.nxfile:
                self._value = self.nxfile.readpath(self.nxpath)
                self._infile = self._saved = True
            else:
                raise IOError("Data is not attached to a file")

    def convert(self, units=""):
        """
        Return the data in particular units.
        """
        try:
            import units
        except ImportError:
            raise NeXusError("No conversion utility available")
        if self._value is not None:
            return self._converter(self._value,units)
        else:
            return None

    def __str__(self):
        """
        If value is loaded, return the value as a string.  If value is
        not loaded, return the empty string.  Only the first view values
        for large arrays will be printed.
        """
        if self._value is not None:
            return str(self._value)
        return ""

    def _str_value(self,indent=0):
        v = str(self)
        if '\n' in v:
            v = '\n'.join([(" "*indent)+s for s in v.split('\n')])
        return v

    def _str_tree(self,indent=0,attrs=False,recursive=False):
        dims = 'x'.join([str(n) for n in self.shape])
        s = str(self)
        if '\n' in s or s == "":
            s = "%s(%s)"%(self.dtype, dims)
        v=[" "*indent + "%s = %s"%(self.nxname, s)]
        if attrs and self.attrs: v.append(self._str_attrs(indent=indent+2))
        return "\n".join(v)

    def walk(self):
        yield self

    def _getaxes(self):
        """
        Return a list of NXfields containing axes.

        Only works if the NXfield has the 'axes' attribute
        """
        try:
            return [getattr(self.nxgroup,name) for name in _readaxes(self.axes)]
        except KeyError:
            return None

    def _getdata(self):
        """
        Return the data if it is not larger than NX_MEMORY.
        """
        if self._value is None:
            if self.nxfile:
                if str(self.dtype) == 'char':
                    self._value = self.nxfile.readpath(self.nxpath)
                elif np.prod(self.shape) * np.dtype(self.dtype).itemsize <= NX_MEMORY*1024*1024:
                    self._value = self.nxfile.readpath(self.nxpath)
                else:
                    raise MemoryError('Data size larger than NX_MEMORY=%s MB' % NX_MEMORY)
                self._saved = True
            else:
                return None

        return self._value

    def _setdata(self, value):
        if value is not None:
            if str(self._dtype) == 'char' or isinstance(value,str):
                self._value = str(value)
                self._shape = (len(self._value),)
                self._dtype = 'char'
            else:
                if self.dtype in np.typeDict:
                    self._value = np.array(value,self.dtype)
                else:
                    self._value = np.array(value)
                self._shape = self._value.shape
                self._dtype = self._value.dtype
            self._saved = False
            self._changed = True
       
    def _getdtype(self):
        return self._dtype

    def _getshape(self):
        return self._shape

    def _getsize(self):
        return len(self)

    nxdata = property(_getdata,_setdata,doc="The data values")
    nxaxes = property(_getaxes,doc="The plotting axes")
    dtype = property(_getdtype,doc="Data type of NeXus field")
    shape = property(_getshape,doc="Shape of NeXus field")
    size = property(_getsize,doc="Size of NeXus field")

SDS = NXfield # For backward compatibility

def _fixaxes(signal, axes):
    """
    Remove length-one dimensions from plottable data
    """
    shape = list(signal.shape)
    while 1 in shape: shape.remove(1)
    newaxes = []
    for axis in axes:
        if axis.size > 1: newaxes.append(axis)
    return signal.nxdata.view().reshape(shape), newaxes

class PylabPlotter(object):

    """
    Matplotlib plotter class for NeXus data.
    """

    def plot(self, signal, axes, title, errors, fmt, 
             xmin, xmax, ymin, ymax, zmin, zmax, **opts):
        """
        Plot the data entry.

        Raises NeXusError if the data cannot be plotted.
        """
        try:
            import matplotlib.pyplot as plt
        except ImportError:
            raise NeXusError("Default plotting package (matplotlib) not available.")

        over = False
        if "over" in opts.keys():
            if opts["over"]: over = True
            del opts["over"]

        log = logx = logy = False
        if "log" in opts.keys():
            if opts["log"]: log = True
            del opts["log"]
        if "logy" in opts.keys():
            if opts["logy"]: logy = True
            del opts["logy"]
        if "logx" in opts.keys():
            if opts["logx"]: logx = True
            del opts["logx"]

        if over:
            plt.autoscale(enable=False)
        else:
            plt.autoscale(enable=True)
            plt.clf()

        # Provide a new view of the data if there is a dimension of length 1
        if 1 in signal.shape:
            data, axes = _fixaxes(signal, axes)
        else:
            data = signal.nxdata

        # Find the centers of the bins for histogrammed data
        axis_data = centers(data, axes)

        #One-dimensional Plot
        if len(data.shape) == 1:
            plt.ioff()
            if hasattr(signal, 'units'):
                if not errors and signal.units == 'counts':
                    errors = NXfield(np.sqrt(data))
            if errors:
                ebars = errors.nxdata
                plt.errorbar(axis_data[0], data, ebars, fmt=fmt, **opts)
            else:
                plt.plot(axis_data[0], data, fmt, **opts)
            if not over:
                ax = plt.gca()
                xlo, xhi = ax.set_xlim(auto=True)        
                ylo, yhi = ax.set_ylim(auto=True)                
                if xmin: xlo = xmin
                if xmax: xhi = xmax
                ax.set_xlim(xlo, xhi)
                if ymin: ylo = ymin
                if ymax: yhi = ymax
                ax.set_ylim(ylo, yhi)
                if logx: ax.set_xscale('symlog')
                if log or logy: ax.set_yscale('symlog')
                plt.xlabel(label(axes[0]))
                plt.ylabel(label(signal))
                plt.title(title)
            plt.ion()

        #Two dimensional plot
        else:
            from matplotlib.image import NonUniformImage
            from matplotlib.colors import LogNorm

            if len(data.shape) > 2:
                slab = [slice(None), slice(None)]
                for _dim in data.shape[2:]:
                    slab.append(0)
                data = data[slab].view().reshape(data.shape[:2])
                print "Warning: Only the top 2D slice of the data is plotted"

            x = axis_data[0]
            y = axis_data[1]
            if not zmin: zmin = np.min(data)
            if not zmax: zmax = np.max(data)
            z = np.clip(data,zmin,zmax).T
            
            if log:
                opts["norm"] = LogNorm()
                if z.min() <= 0 and np.issubdtype(z[0,0],int):
                    z = np.clip(z,0.1,zmax)

            ax = plt.gca()
            extent = (x[0],x[-1],y[0],y[-1])
            im = NonUniformImage(ax, extent=extent, origin=None, **opts)
            im.set_data(x,y,z)
            ax.images.append(im)
            xlo, xhi = ax.set_xlim(x[0],x[-1])
            ylo, yhi = ax.set_ylim(y[0],y[-1])
            if xmin: 
                xlo = xmin
            else:
                xlo = x[0]
            if xmax: 
                xhi = xmax
            else:
                xhi = x[-1]
            if ymin: 
                yhi = ymin
            else:
                yhi = y[0]
            if ymax: 
                yhi = ymax
            else:
                yhi = y[-1]
            ax.set_xlim(xlo, xhi)
            ax.set_ylim(ylo, yhi)
            plt.xlabel(label(axes[0]))
            plt.ylabel(label(axes[1]))
            plt.title(title)
            plt.colorbar(im)

        plt.gcf().canvas.draw_idle()

    @staticmethod
    def show():
        import matplotlib.pyplot as plt
        plt.show()    


class NXgroup(NXobject):

    """
    A NeXus group object.

    This is a subclass of NXobject and is the base class for the specific
    NeXus group classes, e.g., NXentry, NXsample, NXdata.

    NXgroup(*items, **opts)

    Parameters
    ----------
    The NXgroup parameters consist of a list of positional and/or keyword
    arguments.

    Positional Arguments : These must be valid NeXus objects, either an NXfield
    or a NeXus group. These are added without modification as children of this
    group.

    Keyword Arguments : Apart from a list of special keywords shown below,
    keyword arguments are used to add children to the group using the keywords
    as attribute names. The values can either be valid NXfields or NXgroups,
    in which case the 'name' attribute is changed to the keyword, or they
    can be numerical or string data, which are converted to NXfield objects.

    Special Keyword Arguments:

    name : string
        The name of the NXgroup, which is directly accessible as the NXgroup
        attribute 'name'. If the NXgroup is initialized as the attribute of
        a parent group, the name is automatically set to the name of this
        attribute. If 'nxclass' is specified and has the usual prefix 'NX',
        the default name is the class name without this prefix.
    nxclass : string
        The class of the NXgroup.
    entries : dict
        A dictionary containing a list of group entries. This is an
        alternative way of adding group entries to the use of keyword
        arguments.
    file : filename
        The file from which the NXfield has been read.
    path : string
        The path to this object with respect to the root of the NeXus tree,
        using the convention for unix file paths.
    group : NXobject (NXgroup or subclass of NXgroup)
        The parent NeXus group, which is accessible as the group attribute
        'group'. If the group is initialized as the attribute of
        a parent group, this is set to the parent group.

    Python Attributes
    -----------------
    nxclass : string
        The class of the NXobject.
    nxname : string
        The name of the NXfield.
    entries : dictionary
        A dictionary of all the NeXus objects contained within an NXgroup.
    attrs : dictionary
        A dictionary of all the NeXus attributes, i.e., attribute with class NXattr.
    entries : dictionary
        A dictionary of all the NeXus objects contained within the group.
    attrs : dictionary
        A dictionary of all the group's NeXus attributes, which all have the
        class NXattr.
    nxpath : string
        The path to this object with respect to the root of the NeXus tree. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.
    nxroot : NXgroup
        The root object of the NeXus tree containing this object. For
        NeXus data read from a file, this will be a group of class NXroot, but
        if the NeXus tree was defined interactively, it can be any valid
        NXgroup.

    NeXus Group Entries
    -------------------
    Just as in a NeXus file, NeXus groups can contain either data or other
    groups, represented by NXfield and NXgroup objects respectively. To
    distinguish them from regular Python attributes, all NeXus objects are
    stored in the 'entries' dictionary of the NXgroup. However, they can usually
    be assigned or referenced as if they are Python attributes, i.e., using the
    dictionary name directly as the group attribute name, as long as this name
    is not the same as one of the Python attributes defined above or as one of
    the NXfield Python attributes.

    a) Assigning a NeXus object to a NeXus group

    In the example below, after assigning the NXgroup, the following three
    NeXus object assignments to entry.sample are all equivalent:

        >>> entry.sample = NXsample()
        >>> entry.sample['temperature'] = NXfield(40.0)
        >>> entry.sample.temperature = NXfield(40.0)
        >>> entry.sample.temperature = 40.0
        >>> entry.sample.temperature
        NXfield(40.0)

    If the assigned value is not a valid NXobject, then it is cast as an NXfield
    with a type determined from the Python data type.

        >>> entry.sample.temperature = 40.0
        >>> entry.sample.temperature
        NXfield(40.0)
        >>> entry.data.data.x=np.linspace(0,10,11).astype('float32')
        >>> entry.data.data.x
        NXfield([  0.   1.   2. ...,   8.   9.  10.])

    b) Referencing a NeXus object in a NeXus group

    If the name of the NeXus object is not the same as any of the Python
    attributes listed above, or the methods listed below, they can be referenced
    as if they were a Python attribute of the NXgroup. However, it is only possible
    to reference attributes with one of the proscribed names using the group
    dictionary, i.e.,

        >>> entry.sample.tree = 100.0
        >>> print entry.sample.tree
        sample:NXsample
          tree = 100.0
        >>> entry.sample['tree']
        NXfield(100.0)

    For this reason, it is recommended to use the group dictionary to reference
    all group objects within Python scripts.

    NeXus Attributes
    ----------------
    NeXus attributes are not currently used much with NXgroups, except for the
    root group, which has a number of global attributes to store the file name,
    file creation time, and NeXus and HDF version numbers. However, the
    mechanism described for NXfields works here as well. All NeXus attributes
    are stored in the 'attrs' dictionary of the NXgroup, but can be referenced
    as if they are Python attributes as long as there is no name clash.

        >>> entry.sample.temperature = 40.0
        >>> entry.sample.attrs['tree'] = 10.0
        >>> print entry.sample.tree
        sample:NXsample
          @tree = 10.0
          temperature = 40.0
        >>> entry.sample.attrs['tree']
        NXattr(10.0)

    Methods
    -------
    insert(self, NXobject, name='unknown'):
        Insert a valid NXobject (NXfield or NXgroup) into the group.

        If NXobject has a 'name' attribute and the 'name' keyword is not given,
        then the object is inserted with the NXobject name.

    makelink(self, NXobject):
        Add the NXobject to the group entries as a link (NXlink).

    dir(self, attrs=False, recursive=False):
        Print the group directory.

        The directory is a list of NeXus objects within this group, either NeXus
        groups or NXfield data. If 'attrs' is True, NXfield attributes are
        displayed. If 'recursive' is True, the contents of child groups are also
        displayed.

    tree:
        Return the group tree.

        It invokes the 'dir' method with both 'attrs' and 'recursive'
        set to True.

    save(self, filename, format='w5')
        Save the NeXus group into a file

        The object is wrapped in an NXroot group (with name 'root') and an
        NXentry group (with name 'entry'), if necessary, in order to produce
        a valid NeXus file.

    Examples
    --------
    >>> x = NXfield(np.linspace(0,2*np.pi,101), units='degree')
    >>> entry = NXgroup(x, name='entry', nxclass='NXentry')
    >>> entry.sample = NXgroup(temperature=NXfield(40.0,units='K'),
                               nxclass='NXsample')
    >>> print entry.sample.tree
    sample:NXsample
      temperature = 40.0
        @units = K

    Note: All the currently defined NeXus classes are defined as subclasses
          of the NXgroup class. It is recommended that these are used
          directly, so that the above examples become:

    >>> entry = NXentry(x)
    >>> entry.sample = NXsample(temperature=NXfield(40.0,units='K'))

    or

    >>> entry.sample.temperature = 40.0
    >>> entry.sample.temperature.units='K'

    """

    # Plotter to use for plot calls
    _plotter = PylabPlotter()

    def __init__(self, *items, **opts):
        if "name" in opts.keys():
            self._name = opts["name"].replace(' ','_')
            del opts["name"]
        self._entries = {}
        if "entries" in opts.keys():
            for k,v in opts["entries"].items():
                setattr(self, k, v)
            del opts["entries"]
        self._attrs = AttrDict()
        if "attrs" in opts.keys():
            self._setattrs(opts["attrs"])
            del opts["attrs"]
        if "nxclass" in opts.keys():
            self._class = opts["nxclass"]
            del opts["nxclass"]
        if "group" in opts.keys():
            self._group = opts["group"]
            del opts["group"]
        for k,v in opts.items():
            setattr(self, k, v)
        if self.nxclass.startswith("NX"):
            if self.nxname == "unknown": self._name = self.nxclass[2:]
            try: # If one exists, set the class to a valid NXgroup subclass
                self.__class__ = globals()[self.nxclass]
            except KeyError:
                pass
        for item in items:
            try:
                setattr(self, item.nxname, item)
            except AttributeError:
                raise NeXusError("Non-keyword arguments must be valid NXobjects")
        self._saved = False
        self._changed = True

#    def __cmp__(self, other):
#        """Sort groups by their distances or names."""
#        try:
#            return cmp(self.distance, other.distance)
#        except KeyError:
#            return cmp(self.nxname, other.nxname)

    def __repr__(self):
        return "%s('%s')" % (self.__class__.__name__,self.nxname)

    def _str_value(self,indent=0):
        return ""

    def walk(self):
        yield self
        for node in self.entries.values():
            for child in node.walk():
                yield child

    def __getattr__(self, key):
        """
        Provide direct access to groups via nxclass name.
        """
        if key.startswith('NX'):
            return self.component(key)
        elif key in self.entries:
            return self.entries[key]
        elif key in self.attrs:
            return self.attrs[key].nxdata
        raise KeyError(key+" not in "+self.nxclass+":"+self.nxname)

    def __setattr__(self, name, value):
        """
        Set an attribute as an object or regular Python attribute.

        It is assumed that attributes starting with 'nx' or '_' are regular
        Python attributes. All other attributes are converted to valid NXobjects,
        with class NXfield, NXgroup, or a sub-class of NXgroup, depending on the
        assigned value.

        The internal value of the attribute name, i.e., 'name', is set to the
        attribute name used in the assignment.  The parent group of the
        attribute, i.e., 'group', is set to the parent group of the attribute.

        If the assigned value is a numerical (scalar or array) or string object,
        it is converted to an object of class NXfield, whose attribute, 'nxdata',
        is set to the assigned value.
        """
        if name.startswith('_') or name.startswith('nx'):
            object.__setattr__(self, name, value)
        elif isinstance(value, NXattr):
            self._attrs[name] = value
            self._saved = False
            self._changed = True
        else:
            self[name] = value

    def __getitem__(self, index):
        """
        Returns a slice from the NXgroup nxsignal attribute (if it exists) as
        a new NXdata group, if the index is a slice object.

        In most cases, the slice values are applied to the NXfield nxdata array
        and returned within an NXfield object with the same metadata. However,
        if the array is one-dimensional and the index start and stop values
        are real, the nxdata array is returned with values between the limits
        set by those axis values.
        This is to allow axis arrays to be limited by their actual value. This
        real-space slicing should only be used on monotonically increasing (or
        decreasing) one-dimensional arrays.
        """
        if isinstance(index, str): #i.e., requesting a dictionary value
            return self._entries[index]

        if not self.nxsignal:
            raise NeXusError("No plottable signal")
        if not hasattr(self,"nxclass"):
            raise NeXusError("Indexing not allowed for groups of unknown class")
        if isinstance(index, int):
            axes = self.nxaxes
            axes[0] = axes[0][index]
            result = NXdata(self.nxsignal[index], axes)
            if self.nxerrors: result.errors = self.errors[index]
        elif isinstance(index, slice):
            axes = self.nxaxes
            axes[0] = axes[0][index]
            if isinstance(index.start, float) or isinstance(index.stop, float):
                index = slice(self.nxaxes[0].index(index.start),
                              self.nxaxes[0].index(index.stop,max=True)+1)
                result = NXdata(self.nxsignal[index], axes)
                if self.nxerrors: result.errors = self.errors[index]
            else:
                result = NXdata(self.nxsignal[index], axes)
                if self.nxerrors: result.errors = self.errors[index]
        else:
            i = 0
            slices = []
            axes = self.nxaxes
            for ind in index:
                axes[i] = axes[i][ind]
                if isinstance(ind, slice) and \
                   (isinstance(ind.start, float) or isinstance(ind.stop, float)):
                    slices.append(slice(self.nxaxes[i].index(ind.start),
                                        self.nxaxes[i].index(ind.stop)))
                else:
                    slices.append(ind)
                i = i + 1
            result = NXdata(self.nxsignal.__getitem__(tuple(slices)), axes)
            if self.nxerrors: result.errors = self.errors.__getitem__(tuple(slices))
        axes = []
        for axis in result.nxaxes:
            if len(axis) > 1: axes.append(axis)
        result.nxsignal.axes = ":".join([axis.nxname for axis in axes])
        if self.nxtitle:
            result.title = self.nxtitle
        return result

    def __setitem__(self, key, value):
        """
        Adds or modifies an item in the NeXus group.
        """
        if key in self.entries: 
            infile = self._entries[key]._infile
            if isinstance(self._entries[key], NXlink):
                if self._entries[key].nxlink:
                    setattr(self._entries[key].nxlink.nxgroup, key, value)
                return
            attrs = self._entries[key].attrs
        else:
            infile = None
            attrs = {}
        if isinstance(value, NXlink):
            self._entries[key] = value
        elif isinstance(value, NXobject):
            if value.nxgroup is not None:
                memo = {}
                value = deepcopy(value, memo)
                value._attrs = copy(value._attrs)
            value._group = self
            value._name = key
            self._entries[key] = value
        else:
            self._entries[key] = NXfield(value=value, name=key, group=self, attrs=attrs)
        if infile is not None: self[key]._infile = infile
        self._changed = True

    def __deepcopy__(self, memo):
        dpcpy = self.__class__()
        memo[id(self)] = dpcpy
        for k,v in self.items():
            if isinstance(v, NXgroup):
                dpcpy[k] = deepcopy(v, memo)
            else:
                dpcpy[k] = copy(v)
        for k, v in self.attrs.items():
            dpcpy.attrs[k] = copy(v)
        return dpcpy

    def keys(self):
        """
        Returns the names of NeXus objects in the group.
        """
        return self._entries.keys()

    def values(self):
        """
        Returns the values of NeXus objects in the group.
        """
        return self._entries.values()

    def items(self):
        """
        Returns a list of the NeXus objects in the group as (key,value) pairs.
        """
        return self._entries.items()

    def has_key(self, name):
        """
        Returns true if the NeXus object with the specified name is in the group.
        """
        return self._entries.has_key(name)

    def insert(self, value, name='unknown'):
        """
        Adds an attribute to the group.

        If it is not a valid NeXus object (NXfield or NXgroup), the attribute
        is converted to an NXfield.
        """
        if isinstance(value, NXobject):
            if name == 'unknown': name = value.nxname
            if name in self._entries:
                raise NeXusError("'%s' already exists in group" % name)
            value._group = self
            self._entries[name] = value
        else:
            self._entries[name] = NXfield(value=value, name=name, group=self)

    def makelink(self, target):
        """
        Creates a linked NXobject within the group.

        All attributes are inherited from the parent object including the name
        """
        if isinstance(target, NXobject):
            self[target.nxname] = NXlink(target=target, group=self)
        else:
            raise NeXusError("Link target must be an NXobject")

    def read(self):
        """
        Read the NXgroup and all its children from the NeXus file.
        """
        if self.nxfile:
            with self as path:
                n, nxname, nxclass = path.getgroupinfo()
                if nxclass != self.nxclass:
                    raise NeXusError("The NeXus group class does not match the file")
                self._setattrs(path.getattrs())
                entries = path.entries()
            for name,nxclass in entries:
                path = self.nxpath + '/' + name
                if nxclass == 'SDS':
                    attrs = self.nxfile.getattrs()
                    if 'target' in attrs and attrs['target'] != path:
                        self._entries[name] = NXlinkfield(target=attrs['target'])            
                    else:
                        self._entries[name] = NXfield(name=name)
                else:
                    attrs = self.nxfile.getattrs()
                    if 'target' in attrs and attrs['target'] != path:
                        self._entries[name] = NXlinkgroup(name=name,
                                                          target=attrs['target'])
                    else:
                        self._entries[name] = NXgroup(nxclass=nxclass)
                self._entries[name]._group = self
            #Make sure non-linked variables are processed first.
            for entry in self._entries.values():
                for node in entry.walk():
                    if not isinstance(node, NXlink): node.read()
            for entry in self._entries.values():
                for node in entry.walk():
                    if isinstance(node, NXlink): node.read()
            self._infile = self._saved = self._changed = True
        else:
            raise IOError("Data is not attached to a file")

    def write(self):
        """
        Write the NXgroup, including its children, to the NeXus file.
        """
        if self.nxfile:
            if self.nxfile.mode == napi.ACC_READ:
                raise NeXusError("NeXus file is readonly")
            if not self.infile:
                with self.nxgroup as path:
                    path.makegroup(self.nxname, self.nxclass)
                self._infile = True
            with self as path:
                path._writeattrs(self.attrs)
                for entry in self.walk():
                    if entry is not self: entry.write()
                self._infile = self._saved = True
        else:
            raise IOError("Group is not attached to a file")

    def sum(self, axis=None):
        """
        Return the sum of the NXdata group using the Numpy sum method
        on the NXdata signal.

        The result contains a copy of all the metadata contained in
        the NXdata group.
        """
        if not self.nxsignal:
            raise NeXusError("No signal to sum")
        if not hasattr(self,"nxclass"):
            raise NeXusError("Summing not allowed for groups of unknown class")
        if axis is None:
            return self.nxsignal.sum()
        else:
            signal = NXfield(self.nxsignal.sum(axis), name=self.nxsignal.nxname)
            axes = self.nxaxes
            summedaxis = axes.pop(axis)
            units = ""
            if hasattr(summedaxis, "units"): units = summedaxis.units
            signal.long_name = "Integral from %s to %s %s" % \
                               (summedaxis[0], summedaxis[-1], units)
            average = NXfield(0.5*(summedaxis.nxdata[0]+summedaxis.nxdata[-1]), 
                                   name=summedaxis.nxname)
            if units: average.units = units
            result = NXdata(signal, axes, average)
            if self.nxerrors:
                errors = np.sqrt((self.nxerrors.nxdata**2).sum(axis))
                result.errors = NXfield(errors, name="errors")
            if self.nxtitle:
                result.title = self.nxtitle
            return result

    def moment(self, order=1):
        """
        Return an NXfield containing the moments of the NXdata group
        assuming the signal is one-dimensional.

        Currently, only the first moment has been defined. Eventually, the
        order of the moment will be defined by the 'order' parameter.
        """
        if not self.nxsignal:
            raise NeXusError("No signal to calculate")
        elif len(self.nxsignal.shape) > 1:
            raise NeXusError("Operation only possible on one-dimensional signals")
        elif order > 1:
            raise NeXusError("Higher moments not yet implemented")
        if not hasattr(self,"nxclass"):
            raise NeXusError("Operation not allowed for groups of unknown class")
        return (centers(self.nxsignal,self.nxaxes)*self.nxsignal).sum() \
                /self.nxsignal.sum()

    def component(self, nxclass):
        """
        Find all child objects that have a particular class.
        """
        return [E for _name,E in self.entries.items() if E.nxclass==nxclass]

    def signals(self):
        """
        Return a dictionary of NXfield's containing signal data.

        The key is the value of the signal attribute.
        """
        signals = {}
        for obj in self.entries.values():
            if 'signal' in obj.attrs:
                signals[obj.nxsignal.nxdata] = obj
        return signals

    def _signal(self):
        """
        Return the NXfield containing the signal data.
        """
        for obj in self.entries.values():
            if 'signal' in obj.attrs and str(obj.signal) == '1':
#                if isinstance(self[obj.nxname],NXlink):
#                    return self[obj.nxname].nxlink
#                else:
                return self[obj.nxname]
        return None
    
    def _set_signal(self, signal):
        """
        Setter for the signal attribute.
        
        The argument should be a valid NXfield within the group.
        """
        self[signal.nxname].signal = NXattr(1)

    def _axes(self):
        """
        Return a list of NXfields containing the axes.
        """
        try:
            return [getattr(self,name) for name in _readaxes(self.nxsignal.axes)]
        except KeyError:
            axes = {}
            for obj in self.entries:
                if 'axis' in getattr(self,obj).attrs:
                    axes[getattr(self,obj).axis] = getattr(self,obj)
            return [axes[key] for key in sorted(axes.keys())]

    def _set_axes(self, axes):
        """
        Setter for the signal attribute.
        
        The argument should be a list of valid NXfields within the group.
        """
        if not isinstance(axes, list):
            axes = [axes]
        self.nxsignal.axes = NXattr(":".join([axis.nxname for axis in axes]))

    def _errors(self):
        """
        Return the NXfield containing the signal errors.
        """
        try:
            return self.entries['errors']
        except KeyError:
            return None

    def _title(self):
        """
        Return the title as a string.

        If there is no title attribute in the string, the parent
        NXentry group in the group's path is searched.
        """
        title = self.nxpath
        if 'title' in self.entries:
            return str(self.title)
        elif self.nxgroup:
            if 'title' in self.nxgroup.entries:
                return str(self.nxgroup.title)
        return self.nxpath

    def _getentries(self):
        return self._entries

    nxsignal = property(_signal, _set_signal, "Signal NXfield within group")
    nxaxes = property(_axes, _set_axes, "List of axes within group")
    nxerrors = property(_errors, "Errors NXfield within group")
    nxtitle = property(_title, "Title for group plot")
    entries = property(_getentries,doc="NeXus objects within group")

    def plot(self, fmt='bo', xmin=None, xmax=None, ymin=None, ymax=None,
             zmin=None, zmax=None, **opts):
        """
        Plot data contained within the group.

        The format argument is used to set the color and type of the
        markers or lines for one-dimensional plots, using the standard 
        matplotlib syntax. The default is set to blue circles. All 
        keyword arguments accepted by matplotlib.pyplot.plot can be
        used to customize the plot.
        
        In addition to the matplotlib keyword arguments, the following
        are defined:
        
            log = True     - plot the intensity on a log scale
            logy = True    - plot the y-axis on a log scale
            logx = True    - plot the x-axis on a log scale
            over = True    - plot on the current figure

        Raises NeXusError if the data could not be plotted.
        """

        group = self
        if self.nxclass == "NXroot":
            group = group.NXentry[0]
        if group.nxclass == "NXentry":
            try:
                group = group.NXdata[0]
            except IndexError:
                raise NeXusError('No NXdata group found')

        # Find a plottable signal
        signal = group.nxsignal
        if not signal:
            raise NeXusError('No plottable signal defined')

        # Find errors
        errors= group.nxerrors

        # Find the associated axes
        axes = group.nxaxes

        # Construct title
        title = group.nxtitle

        # Plot with the available plotter
        group._plotter.plot(signal, axes, title, errors, fmt, 
                            xmin, xmax, ymin, ymax, zmin, zmax, **opts)
    
    def oplot(self, fmt='bo', **opts):
        """
        Plot the data contained within the group over the current figure.
        """
        self.plot(fmt=fmt, over=True, **opts)

    def logplot(self, fmt='bo', xmin=None, xmax=None, ymin=None, ymax=None,
                zmin=None, zmax=None, **opts):
        """
        Plot the data intensity contained within the group on a log scale.
        """
        self.plot(fmt=fmt, log=True,
                  xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                  zmin=zmin, zmax=zmax, **opts)

class NXlink(NXobject):

    """
    Class for NeXus linked objects.

    The real object will be accessible by following the link attribute.
    """

    _class = "NXlink"

    def __init__(self, target=None, name='link', group=None):
        self._group = group
        self._class = "NXlink"
        if isinstance(target, NXobject):
            self._name = target.nxname
            self._target = target.nxpath
            self.nxlink.attrs["target"] = target.nxpath
            if target.nxclass == "NXlink":
                raise NeXusError("Cannot link to another NXlink object")
            elif target.nxclass == "NXfield":
                self.__class__ = NXlinkfield
            else:
                self.__class__ = NXlinkgroup
        else:
            self._name = name
            self._target = target

    def __getattr__(self, key):
        try:
            try:
                return self.nxlink.__dict__[key]
            except KeyError:
                return self.nxlink.__getattr__(key)
        except KeyError:
            raise KeyError((key+" not in %s" % self._target))

    def __setattr__(self, name, value):
        if name.startswith('_')  or name.startswith('nx'):
            object.__setattr__(self, name, value)
        elif self.nxlink:
            self.nxlink.__setattr__(name, value)

    def __repr__(self):
        return "NXlink('%s')"%(self._target)

    def __str__(self):
        return str(self.nxlink)

    def _str_tree(self, indent=0, attrs=False, recursive=False):
        if self.nxlink:
            return self.nxlink._str_tree(indent, attrs, recursive)
        else:
            return " "*indent+self.nxname+' -> '+self._target

    def _getlink(self):
        link = self.nxroot
        if link:
            try:
                for level in self._target[1:].split('/'):
                    link = link.entries[level]
                return link
            except AttributeError:
                return None
        else:
            return None

    def _getattrs(self):
        return self.nxlink.attrs

    nxlink = property(_getlink, "Linked object")
    attrs = property(_getattrs,doc="NeXus attributes for object")

    def read(self):
        """
        Read the linked NXobject.
        """
        self.nxlink.read()
        self._infile = self._saved = self._changed = True


class NXlinkfield(NXlink, NXfield):

    """
    Class for a NeXus linked field.

    The real field will be accessible by following the link attribute.
    """

    def write(self):
        """
        Write the linked NXfield.
        """
        self.nxlink.write()
        if not self.infile:
            with self.nxlink as path:
                target = path.getdataID()
            with self.nxgroup as path:
                path.makelink(target)
            self._infile = self._saved = True

    def get(self, offset, size):
        """
        Get a slab from the data array.

        Offsets are 0-origin.  Shape can be inferred from the data.
        Offset and shape must each have one entry per dimension.

        This operation should be performed in a "with group.data"
        conext.

        Raises ValueError cannot convert units.

        Corresponds to NXgetslab(handle,data,offset,shape)
        """
        if self.nxfile:
            with self.nxlink as path:
                value = path.getslab(offset,size)
        else:
            raise IOError("Data is not attached to a file")

NXlinkdata = NXlinkfield # For backward compatibility

class NXlinkgroup(NXlink, NXgroup):

    """
    Class for a NeXus linked group.

    The real group will be accessible by following the link attribute.
    """

    def write(self):
        """
        Write the linked NXgroup.
        """
        self.nxlink.write()
        if not self.infile:
            with self.nxlink as path:
                target = path.getgroupID()
            with self.nxgroup as path:
                path.makelink(target)
            self._infile = self._saved = True

    def _getentries(self):
        return self.nxlink.entries

    entries = property(_getentries,doc="NeXus objects within group")


class NXentry(NXgroup):

    """
    NXentry group. This is a subclass of the NXgroup class.

    Each NXdata and NXmonitor object of the same name will be added
    together, raising an NeXusError if any of the groups do not exist
    in both NXentry groups or if any of the NXdata additions fail.
    The resulting NXentry group contains a copy of all the other metadata
    contained in the first group. Note that other extensible data, such
    as the run duration, are not currently added together.

    See the NXgroup documentation for more details.
    """

    def __init__(self, *items, **opts):
        self._class = "NXentry"
        NXgroup.__init__(self, *items, **opts)

    def __add__(self, other):
        """
        Add two NXentry objects
        """
        result = NXentry(entries=self.entries, attrs=self.attrs)
        try:
            names = [group.nxname for group in self.component("NXdata")]
            for name in names:
                if isinstance(other.entries[name], NXdata):
                    result.entries[name] = self.entries[name] + other.entries[name]
                else:
                    raise KeyError
            names = [group.nxname for group in self.component("NXmonitor")]
            for name in names:
                if isinstance(other.entries[name], NXmonitor):
                    result.entries[name] = self.entries[name] + other.entries[name]
                else:
                    raise KeyError
            return result
        except KeyError:
            raise NeXusError("Inconsistency between two NXentry groups")

    def __sub__(self, other):
        """
        Subtract two NXentry objects
        """
        result = NXentry(entries=self.entries, attrs=self.attrs)
        try:
            names = [group.nxname for group in self.component("NXdata")]
            for name in names:
                if isinstance(other.entries[name], NXdata):
                    result.entries[name] = self.entries[name] - other.entries[name]
                else:
                    raise KeyError
            names = [group.nxname for group in self.component("NXmonitor")]
            for name in names:
                if isinstance(other.entries[name], NXmonitor):
                    result.entries[name] = self.entries[name] - other.entries[name]
                else:
                    raise KeyError
            return result
        except KeyError:
            raise NeXusError("Inconsistency between two NXentry groups")


class NXsubentry(NXentry):

    """
    NXsubentry group. This is a subclass of the NXsubentry class.

    See the NXgroup documentation for more details.
    """

    def __init__(self, *items, **opts):
        self._class = "NXsubentry"
        NXgroup.__init__(self, *items, **opts)


class NXdata(NXgroup):

    """
    NXdata group. This is a subclass of the NXgroup class.

    The constructor assumes that the first argument contains the signal and
    the second contains either the axis, for one-dimensional data, or a list
    of axes, for multidimensional data. These arguments can either be NXfield
    objects or Numpy arrays, which are converted to NXfield objects with default
    names. Alternatively, the signal and axes NXfields can be defined using the
    'nxsignal' and 'nxaxes' properties. See the examples below.
    
    Various arithmetic operations (addition, subtraction, multiplication,
    and division) have been defined for combining NXdata groups with other
    NXdata groups, Numpy arrays, or constants, raising a NeXusError if the
    shapes don't match. Data errors are propagated in quadrature if
    they are defined, i.e., if the 'nexerrors' attribute is not None,

    Attributes
    ----------
    nxsignal : The NXfield containing the attribute 'signal' with value 1
    nxaxes   : A list of NXfields containing the signal axes
    nxerrors : The NXfield containing the errors

    Methods
    -------
    plot(self, fmt, over=False, log=False, logy=False, logx=False, **opts)
        Plot the NXdata group using the defined signal and axes. Valid
        Matplotlib parameters, specifying markers, colors, etc, can be
        specified using format argument or through keyword arguments.

    logplot(self, fmt, over=False, logy=False, logx=False, **opts)
        Plot the NXdata group using the defined signal and axes with
        the intensity plotted on a logarithmic scale. In one-dimensional
        plots, this is the y-axis. In two-dimensional plots, it is the 
        color scale.

    oplot(self, fmt, **opts)
        Plot the NXdata group using the defined signal and axes over
        the current plot.

    moment(self, order=1)
        Calculate moments of the NXdata group. This assumes that the
        signal is one-dimenional. Currently, only the first moment is
        implemented.

    Examples
    --------
    There are three methods of creating valid NXdata groups with the
    signal and axes NXfields defined according to the NeXus standard.
    
    1) Create the NXdata group with Numpy arrays that will be assigned
       default names.
       
    >>> x = np.linspace(0, 2*np.pi, 101)
    >>> line = NXdata(sin(x), x)
    data:NXdata
      signal = float64(101)
        @axes = x
        @signal = 1
      axis1 = float64(101)
      
    2) Create the NXdata group with NXfields that have their internal
       names already assigned.

    >>> x = NXfield(linspace(0,2*pi,101), name='x')
    >>> y = NXfield(linspace(0,2*pi,101), name='y')    
    >>> X, Y = np.meshgrid(x, y)
    >>> z = NXfield(sin(X) * sin(Y), name='z')
    >>> entry = NXentry()
    >>> entry.grid = NXdata(z, (x, y))
    >>> grid.tree()
    entry:NXentry
      grid:NXdata
        x = float64(101)
        y = float64(101)
        z = float64(101x101)
          @axes = x:y
          @signal = 1

    3) Create the NXdata group with keyword arguments defining the names 
       and set the signal and axes using the nxsignal and nxaxes properties.

    >>> x = linspace(0,2*pi,101)
    >>> y = linspace(0,2*pi,101)  
    >>> X, Y = np.meshgrid(x, y)
    >>> z = sin(X) * sin(Y)
    >>> entry = NXentry()
    >>> entry.grid = NXdata(z=sin(X)*sin(Y), x=x, y=y)
    >>> entry.grid.nxsignal = entry.grid.z
    >>> entry.grid.nxaxes = [entry.grid.x.entry.grid.y]
    >>> grid.tree()
    entry:NXentry
      grid:NXdata
        x = float64(101)
        y = float64(101)
        z = float64(101x101)
          @axes = x:y
          @signal = 1
    """

    def __init__(self, signal=None, axes=None, *items, **opts):
        self._class = "NXdata"
        NXgroup.__init__(self, *items, **opts)
        if signal is not None:
            if isinstance(signal,NXfield):
                if signal.nxname == "unknown": signal.nxname = "signal"
                if "signal" not in signal.attrs: signal.signal = 1
                self[signal.nxname] = signal
                signalname = signal.nxname
            else:
                self["signal"] = signal
                self["signal"].signal = 1
                signalname = "signal"
            if axes is not None:
                if not isinstance(axes,tuple) and not isinstance(axes,list):
                    axes = [axes]
                axisnames = {}
                i = 0
                for axis in axes:
                    i = i + 1
                    if isinstance(axis,NXfield):
                        if axis._name == "unknown": axis._name = "axis%s" % i
                        self[axis.nxname] = axis
                        axisnames[i] = axis.nxname
                    else:
                        axisname = "axis%s" % i
                        self[axisname] = axis
                        axisnames[i] = axisname
                self[signalname].axes = ":".join(axisnames.values())

    def __add__(self, other):
        """
        Define a method for adding a NXdata group to another NXdata group
        or to a number. Only the signal data is affected.

        The result contains a copy of all the metadata contained in
        the first NXdata group. The module checks that the dimensions are
        compatible, but does not check that the NXfield names or values are
        identical. This is so that spelling variations or rounding errors
        do not make the operation fail. However, it is up to the user to
        ensure that the results make sense.
        """
        result = NXdata(entries=self.entries, attrs=self.attrs)
        if isinstance(other, NXdata):
            if self.nxsignal and self.nxsignal.shape == other.nxsignal.shape:
                result.entries[self.nxsignal.nxname] = self.nxsignal + other.nxsignal
                if self.nxerrors:
                    if other.nxerrors:
                        result.errors = np.sqrt(self.errors.nxdata**2+other.errors.nxdata**2)
                    else:
                        result.errors = self.errors
                return result
        elif isinstance(other, NXgroup):
            raise NeXusError("Cannot add two arbitrary groups")
        else:
            result.entries[self.nxsignal.nxname] = self.nxsignal + other
            result.entries[self.nxsignal.nxname].nxname = self.nxsignal.nxname
            return result

    def __sub__(self, other):
        """
        Define a method for subtracting a NXdata group or a number from
        the NXdata group. Only the signal data is affected.

        The result contains a copy of all the metadata contained in
        the first NXdata group. The module checks that the dimensions are
        compatible, but does not check that the NXfield names or values are
        identical. This is so that spelling variations or rounding errors
        do not make the operation fail. However, it is up to the user to
        ensure that the results make sense.
        """
        result = NXdata(entries=self.entries, attrs=self.attrs)
        if isinstance(other, NXdata):
            if self.nxsignal and self.nxsignal.shape == other.nxsignal.shape:
                result.entries[self.nxsignal.nxname] = self.nxsignal - other.nxsignal
                if self.nxerrors:
                    if other.nxerrors:
                        result.errors = np.sqrt(self.errors.nxdata**2+other.errors.nxdata**2)
                    else:
                        result.errors = self.errors
                return result
        elif isinstance(other, NXgroup):
            raise NeXusError("Cannot subtract two arbitrary groups")
        else:
            result.entries[self.nxsignal.nxname] = self.nxsignal - other
            result.entries[self.nxsignal.nxname].nxname = self.nxsignal.nxname
            return result

    def __mul__(self, other):
        """
        Define a method for multiplying the NXdata group with a NXdata group
        or a number. Only the signal data is affected.

        The result contains a copy of all the metadata contained in
        the first NXdata group. The module checks that the dimensions are
        compatible, but does not check that the NXfield names or values are
        identical. This is so that spelling variations or rounding errors
        do not make the operation fail. However, it is up to the user to
        ensure that the results make sense.
        """
        result = NXdata(entries=self.entries, attrs=self.attrs)
        if isinstance(other, NXdata):

            # error here signal not defined in this scope
            #if self.nxsignal and signal.shape == other.nxsignal.shape:
            if self.nxsignal and self.nxsignal.shape == other.nxsignal.shape:
                result.entries[self.nxsignal.nxname] = self.nxsignal * other.nxsignal
                if self.nxerrors:
                    if other.nxerrors:
                        result.errors = np.sqrt((self.errors.nxdata*other.nxsignal.nxdata)**2+
                                                (other.errors.nxdata*self.nxsignal.nxdata)**2)
                    else:
                        result.errors = self.errors
                return result
        elif isinstance(other, NXgroup):
            raise NeXusError("Cannot multiply two arbitrary groups")
        else:
            result.entries[self.nxsignal.nxname] = self.nxsignal * other
            result.entries[self.nxsignal.nxname].nxname = self.nxsignal.nxname
            if self.nxerrors:
                result.errors = self.errors * other
            return result

    def __rmul__(self, other):
        """
        Define a method for multiplying NXdata groups.

        This variant makes __mul__ commutative.
        """
        return self.__mul__(other)

    def __div__(self, other):
        """
        Define a method for dividing the NXdata group by a NXdata group
        or a number. Only the signal data is affected.

        The result contains a copy of all the metadata contained in
        the first NXdata group. The module checks that the dimensions are
        compatible, but does not check that the NXfield names or values are
        identical. This is so that spelling variations or rounding errors
        do not make the operation fail. However, it is up to the user to
        ensure that the results make sense.
        """
        result = NXdata(entries=self.entries, attrs=self.attrs)
        if isinstance(other, NXdata):
            if self.nxsignal and self.nxsignal.shape == other.nxsignal.shape:
                # error here, signal and othersignal not defined here
                #result.entries[self.nxsignal.nxname] = signal / othersignal
                result.entries[self.nxsignal.nxname] = self.nxsignal / other.nxsignal
                resultvalues = result.entries[self.nxsignal.nxname].nxdata
                if self.nxerrors:
                    if other.nxerrors:
                        result.errors = (np.sqrt(self.errors.nxdata**2 +
                                         (resultvalues*other.errors.nxdata)**2)
                                         / other.nxsignal)
                    else:
                        result.errors = self.errors
                return result
        elif isinstance(other, NXgroup):
            raise NeXusError("Cannot divide two arbitrary groups")
        else:
            result.entries[self.nxsignal.nxname] = self.nxsignal / other
            result.entries[self.nxsignal.nxname].nxname = self.nxsignal.nxname
            if self.nxerrors: result.errors = self.errors / other
            return result


class NXmonitor(NXdata):

    """
    NXmonitor group. This is a subclass of the NXdata class.

    See the NXdata and NXgroup documentation for more details.
    """

    def __init__(self, signal=None, axes=(), *items, **opts):
        NXdata.__init__(self, signal=signal, axes=axes, *items, **opts)
        self._class = "NXmonitor"
        if "name" not in opts.keys():
            self._name = "monitor"


class NXlog(NXgroup):

    """
    NXlog group. This is a subclass of the NXgroup class.

    Methods
    -------
    plot(self, **opts)
        Plot the logged values against the elapsed time. Valid
        Matplotlib parameters, specifying markers, colors, etc, can be
        specified using the 'opts' dictionary.

    See the NXgroup documentation for more details.
    """

    def __init__(self, *items, **opts):
        self._class = "NXlog"
        NXgroup.__init__(self, *items, **opts)

    def plot(self, **opts):
        axis = [self.time]
        title = "%s Log" % self.value.nxname.upper()
        self._plotter.plot(self.value, axis, title, **opts)


#-------------------------------------------------------------------------
#Add remaining base classes as subclasses of NXgroup and append to __all__

for _class in _nxclasses:
    if _class not in globals():
        docstring = """
                    %s group. This is a subclass of the NXgroup class.

                    See the NXgroup documentation for more details.
                    """ % _class
        globals()[_class]=type(_class, (NXgroup,),
                               {'_class':_class,'__doc__':docstring})
    __all__.append(_class)

#-------------------------------------------------------------------------


def centers(signal, axes):
    """
    Return the centers of the axes.

    This works regardless if the axes contain bin boundaries or centers.
    """
    def findc(axis, dimlen):
        if axis.shape[0] == dimlen+1:
            return (axis.nxdata[:-1] + axis.nxdata[1:])/2
        else:
            assert axis.shape[0] == dimlen
            return axis.nxdata
    return [findc(a,signal.shape[i]) for i,a in enumerate(axes)]

def setmemory(value):
    """
    Set the memory limit for data arrays (in MB).
    """
    global NX_MEMORY
    NX_MEMORY = value

def label(field):
    """
    Return a label for a data field suitable for use on a graph axis.
    """
    if hasattr(field,'long_name'):
        return field.long_name
    elif hasattr(field,'units'):
        return "%s (%s)"%(field.nxname,field.units)
    else:
        return field.nxname

# File level operations
def load(filename, mode='r'):
    """
    Read a NeXus file returning a tree of objects.

    This is aliased to 'read' because of potential name clashes with Numpy
    """
    file = NeXusTree(filename,mode)
    tree = file.readfile()
    file.close()
    return tree

#Definition for when there are name clashes with Numpy
nxload = load
__all__.append('nxload')

def save(filename, group, format='w5'):
    """
    Write a NeXus file from a tree of objects.
    """
    if group.nxclass == "NXroot":
        tree = group
    elif group.nxclass == "NXentry":
        tree = NXroot(group)
    else:
        tree = NXroot(NXentry(group))
    file = NeXusTree(filename, format)
    file.writefile(tree)
    file.close()

def tree(file):
    """
    Read and summarize the named NeXus file.
    """
    nxfile = load(file)
    nxfile.tree

def demo(argv):
    """
    Process a list of command line commands.

    'argv' should contain program name, command, arguments, where command is one
    of the following:
        copy fromfile.nxs tofile.nxs
        ls f1.nxs f2.nxs ...
    """
    if len(argv) > 1:
        op = argv[1]
    else:
        op = 'help'
    if op == 'ls':
        for f in argv[2:]: dir(f)
    elif op == 'copy' and len(argv)==4:
        tree = load(argv[2])
        save(argv[3], tree)
    elif op == 'plot' and len(argv)==4:
        tree = load(argv[2])
        for entry in argv[3].split('.'):
            tree = getattr(tree,entry)
        tree.plot()
        tree._plotter.show()

    else:
        usage = """
usage: %s cmd [args]
    copy fromfile.nxs tofile.nxs
    ls *.nxs
    plot file.nxs entry.data
        """%(argv[0],)
        print usage


if __name__ == "__main__":
    import sys
    demo(sys.argv)