How to use the prody.utilities.openFile function in ProDy

else:
                self._filename = filename = msa

        if filename is not None:
            self._filename = filename
            title, ext = splitext(split(filename)[1])
            if ext.lower() == '.gz':
                title, ext = splitext(split(title)[1])
            if format is None:
                try:
                    self._format = format = MSAEXTMAP[ext.lower()]
                except KeyError:
                    raise TypeError('format is not specified and could not be '
                                    'determined from file extension')
            self._title = title
            self._stream = openFile(msa, mode)

        else:
            if self._format is None:
                raise ValueError('format must be specified when msa is a '
                                 'stream')
            self._stream = msa
            self._title = 'stream'
            try:
                closed = self._stream.closed
            except AttributeError:
                closed = self._stream.myfileobj.closed
            if closed:
                raise ValueError('msa stream must not be closed')


        self._lenseq = None

if title is None:
            title = pdb
            kwargs['title'] = title
        filename = fetchPDB(pdb, **kwargs)
        if filename is None:
            raise IOError('PDB file for {0} could not be downloaded.'
                          .format(pdb))
        pdb = filename
    if title is None:
        title, ext = os.path.splitext(os.path.split(pdb)[1])
        if ext == '.gz':
            title, ext = os.path.splitext(title)
        if len(title) == 7 and title.startswith('pdb'):
            title = title[3:]
        kwargs['title'] = title
    pdb = openFile(pdb, 'rt')
    if chain != '':
        kwargs['chain'] = chain
    result = parsePDBStream(pdb, **kwargs)
    pdb.close()
    return result

filename = emd + '.map'
            elif os.path.isfile(emd + '.map.gz'):
                filename = emd + '.map.gz'
            else:
                filename = fetchPDB(emd, report=True, format='emd',compressed=False)
                if filename is None:
                    raise IOError('EMD map file for {0} could not be downloaded.'
                                  .format(emd))
            emd = filename
        else:   
            raise IOError('EMD file {0} is not available in the directory {1}'
                           .format(emd, os.getcwd()))
    if title is None:
        kwargs['title'], ext = os.path.splitext(os.path.split(emd)[1])

    emdStream = openFile(emd, 'rb')

    if emd.endswith('.stk'):
        result = parseSTKStream(emd, **kwargs)
    else:
        result = parseEMDStream(emdStream, **kwargs)

    emdStream.close()

    return result

def parseHeatmap(heatmap, **kwargs):
    """Returns a two dimensional array and a dictionary with information parsed
    from *heatmap*, which may be an input stream or an :file:`.hm` file in VMD
    plugin Heat Mapper format."""

    try:
        readline, close = heatmap.readline, lambda: None
    except AttributeError:
        heatmap = openFile(heatmap)
        readline, close = heatmap.readline, heatmap.close

    meta = {}
    arrs = []

    line = readline()
    while line:
        if line.startswith('-'):
            label, data = line[1:].split(None, 1)
            data = data.strip()
            if data[0] == data[-1] == '"':
                data = data[1:-1]
            label = label.strip()
            try:
                meta[label] = HMTYPES[label](data)
            except KeyError:

:type max: float

    Other keyword arguments that are arrays with length equal to the y-axis
    (second dimension of heatmap) will be considered as *numbering*."""
    
    try:
        ndim, shape = heatmap.ndim, heatmap.shape
    except:
        raise TypeError('heatmap must be an array object')
    if ndim!= 2:
        raise TypeError('heatmap must be a 2D array')
    
    try:
        write, close = filename.write, lambda: None
    except AttributeError: 
        out = openFile(filename, 'wb')
        write, close = out.write, out.close
    
    write('-min "{0}"\n'.format(kwargs.pop('min', heatmap.min())))
    write('-max "{0}"\n'.format(kwargs.pop('max', heatmap.max())))
    for label, default in [
        ('title', 'unknown'),
        ('xlabel', 'unknown'),
        ('xorigin', 0),
        ('xstep', 1),
        ('ylabel', 'unknown'),
    ]:
        write('-{0} "{1}"\n'.format(label, kwargs.pop(label, default)))
    
    numbering = []
    numlabels = []
    for key, val in kwargs.items():

if not xml:
            #'http://www.pdb.org/pdb/files/ligand/{0}.xml'
            try:
                inp = openURL(url)
            except IOError:
                raise IOError('XML file for ligand {0} is not found online'
                              .format(cci))
            else:
                xml = inp.read()
                inp.close()
            if filename:
                out = openFile(filename, mode='w', folder=folder)
                out.write(xml)
                out.close()
            if SETTINGS.get('ligand_xml_save'):
                with openFile(xmlgz, 'w') as out:
                    out.write(xml)

    import xml.etree.cElementTree as ET

    root = ET.XML(xml)
    if (root.get('{http://www.w3.org/2001/XMLSchema-instance}'
                 'schemaLocation') !=
            'http://pdbml.pdb.org/schema/pdbx-v40.xsd pdbx-v40.xsd'):
        LOGGER.warn('XML is not in PDBx/PDBML v 4.0 format, resulting '
                    'dictionary may not contain all data fields')
    ns = root.tag[:root.tag.rfind('}')+1]
    len_ns = len(ns)
    dict_ = {'url': url, 'path': path}

    for child in list(root.find(ns + 'chem_compCategory')[0]):
        tag = child.tag[len_ns:]

raise TypeError('model must be a 3-dimensional NMA instance')
    elif len(model) == 0:
        raise ValueError('model must have normal modes calculated')
    elif model.getStiffness() is None:
        raise ValueError('model must have stiffness matrix calculated')
    elif len(indices)==0:
        raise ValueError('indices cannot be an empty array')

    if len(indices)==1:
        indices0=indices[0]-resnum_list[0]
        indices1=indices[0]-resnum_list[0]
    elif len(indices)==2:
        indices0=indices[0]-resnum_list[0]
        indices1=indices[1]-resnum_list[0]

    out = openFile(addext(filename, '.tcl'), 'w')
    out_txt = openFile(addext(filename,'.txt'), 'w')
    writePDB(filename + '.pdb', pdb)

    LOGGER.info('Creating VMD file.')
    
    out.write('display rendermode GLSL \n')
    out.write('display projection orthographic\n')
    out.write('color Display Background white\n')
    out.write('display shadows on\n')
    out.write('display depthcue off\n')
    out.write('axes location off\n')
    out.write('stage location off\n')
    out.write('light 0 on\n')
    out.write('light 1 on\n')
    out.write('light 2 off\n')
    out.write('light 3 on\n')

if attr == '_modesets':
                value = list(value)
                value.append(None)
            attr_dict[attr] = value

    if filename is None:
        filename = mode_ensemble.getTitle().replace(' ', '_')
    
    suffix = '.modeens'
    if not filename.lower().endswith('.npz'):
        if not filename.lower().endswith(suffix):
            filename += suffix + '.npz'
        else:
            filename += '.npz'
            
    ostream = openFile(filename, 'wb', **kwargs)
    np.savez_compressed(ostream, **attr_dict)
    ostream.close()

    return filename

extend + '.nmd'), *extended)

    outall = kwargs.get('outall')
    delim = kwargs.get('numdelim')
    ext = kwargs.get('numext')
    format = kwargs.get('numformat')

    if outall or kwargs.get('outeig'):
        prody.writeArray(join(outdir, prefix + '_evectors'+ext),
                         gnm.getArray(), delimiter=delim, format=format)
        prody.writeArray(join(outdir, prefix + '_evalues'+ext),
                         gnm.getEigvals(), delimiter=delim, format=format)

    if outall or kwargs.get('outbeta'):
        from prody.utilities import openFile
        fout = openFile(prefix + '_beta.txt', 'w', folder=outdir)
        fout.write('{0[0]:1s} {0[1]:4s} {0[2]:4s} {0[3]:5s} {0[4]:5s}\n'
                       .format(['C', 'RES', '####', 'Exp.', 'The.']))
        for data in zip(select.getChids(), select.getResnames(),
                        select.getResnums(), select.getBetas(),
                        prody.calcTempFactors(gnm, select)):
            fout.write('{0[0]:1s} {0[1]:4s} {0[2]:4d} {0[3]:5.2f} {0[4]:5.2f}\n'
                       .format(data))
        fout.close()

    if outall or kwargs.get('outcov'):
        prody.writeArray(join(outdir, prefix + '_covariance'+ext),
                         gnm.getCovariance(), delimiter=delim, format=format)

    if outall or kwargs.get('outcc') or kwargs.get('outhm'):
        cc = prody.calcCrossCorr(gnm)
        if outall or kwargs.get('outcc'):

if matrices:
            attr_dict['_project'] = nma._project

    if isinstance(nma, imANM):
        attr_dict['type'] = 'imANM'

    if isinstance(nma, exANM):
        attr_dict['type'] = 'exANM'

    suffix = '.' + attr_dict['type'].lower()
    if not filename.lower().endswith('.npz'):
        if not filename.lower().endswith(suffix):
            filename += suffix + '.npz'
        else:
            filename += '.npz'
    ostream = openFile(filename, 'wb', **kwargs)
    np.savez(ostream, **attr_dict)
    ostream.close()
    return filename