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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def copy(self, other, ignore=None, parameters=None, parameter_names=None, read_args=None, write_args=None):
 """Copies metadata, info, and samples in this file to another file. Parameters other : str or InferenceFile The file to write to. May be either a string giving a filename, or an open hdf file. If the former, the file will be opened with the write attribute (note that if a file already exists with that name, it will be deleted). ignore : (list of) strings Don't copy the given groups. If the samples group is included, no samples will be copied. parameters : list of str, optional List of parameters in the samples group to copy. If None, will copy all parameters. parameter_names : dict, optional Rename one or more parameters to the given name. The dictionary should map parameter -> parameter name. If None, will just use the original parameter names. read_args : dict, optional Arguments to pass to ``read_samples``. write_args : dict, optional Arguments to pass to ``write_samples``. Returns ------- InferenceFile The open file handler to other. """

        if not isinstance(other, h5py.File):
            # check that we're not trying to overwrite this file
            if other == self.name:
                raise IOError("destination is the same as this file")
            other = self.__class__(other, 'w')
        # metadata
        self.copy_metadata(other)
        # info
        if ignore is None:
            ignore = []
        if isinstance(ignore, (str, unicode)):
            ignore = [ignore]
        self.copy_info(other, ignore=ignore)
        # samples
        if self.samples_group not in ignore:
            self.copy_samples(other, parameters=parameters,
                              parameter_names=parameter_names,
                              read_args=read_args,
                              write_args=write_args)
            # if any down selection was done, re-set the default
            # thin-start/interval/end
            p = self[self.samples_group].keys()[0]
            my_shape = self[self.samples_group][p].shape
            p = other[other.samples_group].keys()[0]
            other_shape = other[other.samples_group][p].shape
            if my_shape != other_shape:
                other.attrs['thin_start'] = 0
                other.attrs['thin_interval'] = 1
                other.attrs['thin_end'] = None
        return other