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Complete this python program:
def create_fixed_effects_flow(name='fixedfx'):
assistant
#Here is the Python code you requested.

    """Create a fixed-effects workflow
    This workflow is used to combine registered copes and varcopes across runs
    for an individual subject
    Example
    >>> fixedfx = create_fixed_effects_flow()
    >>> fixedfx.base_dir = \.\
    >>> fixedfx.inputs.inputspec.copes = [[\cope1run1.nii.gz\, \cope1run2.nii.gz\], [\cope2run1.nii.gz\, \cope2run2.nii.gz\]] # per contrast
    >>> fixedfx.inputs.inputspec.varcopes = [[\varcope1run1.nii.gz\, \varcope1run2.nii.gz\], [\varcope2run1.nii.gz\, \varcope2run2.nii.gz\]] # per contrast
    >>> fixedfx.inputs.inputspec.dof_files = [\dofrun1\, \dofrun2\] # per run
    >>> fixedfx.run() #doctest: +SKIP
    Inputs::
    inputspec.copes : list of list of cope files (one list per contrast)
    inputspec.varcopes : list of list of varcope files (one list per
    contrast)
    inputspec.dof_files : degrees of freedom files for each run
    Outputs::
    outputspec.res4d : 4d residual time series
    outputspec.copes : contrast parameter estimates
    outputspec.varcopes : variance of contrast parameter estimates
    outputspec.zstats : z statistics of contrasts
    outputspec.tstats : t statistics of contrasts
    """
    fixed_fx = pe.Workflow(name=name)
    inputspec = pe.Node(util.IdentityInterface(fields=['copes', 'varcopes', 'dof_files']), name='inputspec')
    '\n                Use    :class:`nipype.interfaces.fsl.Merge`    to    merge    the    copes    and\n                varcopes    for    each    condition\n                '
    copemerge = pe.MapNode(interface=fsl.Merge(dimension='t'), iterfield=['in_files'], name='copemerge')
    varcopemerge = pe.MapNode(interface=fsl.Merge(dimension='t'), iterfield=['in_files'], name='varcopemerge')
    '\n                Use    :class:`nipype.interfaces.fsl.L2Model`    to    generate    subject    and    condition\n                specific    level    2    model    design    files\n                '
    level2model = pe.Node(interface=fsl.L2Model(), name='l2model')
    '\n                Use    :class:`nipype.interfaces.fsl.FLAMEO`    to    estimate    a    second    level    model\n                '
    flameo = pe.MapNode(interface=fsl.FLAMEO(run_mode='fe'), name='flameo', iterfield=['cope_file', 'var_cope_file'])
    def get_dofvolumes(dof_files, cope_files):
        import os
        import nibabel as nb
        import numpy as np
        img = nb.load(cope_files[0])
        if (len(img.shape) > 3):
            out_data = np.zeros(img.shape)
        else:
            out_data = np.zeros((list(img.shape) + [1]))
        for i in range(out_data.shape[(-1)]):
            dof = np.loadtxt(dof_files[i])
            out_data[:, :, :, i] = dof
        filename = os.path.join(os.getcwd(), 'dof_file.nii.gz')
        newimg = nb.Nifti1Image(out_data, None, img.header)
        newimg.to_filename(filename)
        return filename
    gendof = pe.Node(util.Function(input_names=['dof_files', 'cope_files'], output_names=['dof_volume'], function=get_dofvolumes), name='gendofvolume')
    outputspec = pe.Node(util.IdentityInterface(fields=['res4d', 'copes', 'varcopes', 'zstats', 'tstats']), name='outputspec')
    fixed_fx.connect([(inputspec, copemerge, [('copes', 'in_files')]),...