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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 write_to_hdf(self, fp, template_hash, root=None, precision=None):
 """Write the compressed waveform to the given hdf file handler. The waveform is written to: `fp['[{root}/]compressed_waveforms/{template_hash}/{param}']`, where `param` is the `sample_points`, `amplitude`, and `phase`. The `interpolation`, `tolerance`, `mismatch` and `precision` are saved to the group's attributes. Parameters fp : h5py.File An open hdf file to write the compressed waveform to. template_hash : {hash, int, str} A hash, int, or string to map the template to the waveform. root : {None, str} Put the `compressed_waveforms` group in the given directory in the hdf file. If `None`, `compressed_waveforms` will be the root directory. precision : {None, str} Cast the saved parameters to the given precision before saving. If None provided, will use whatever their current precision is. This will raise an error if the parameters have single precision but the requested precision is double. """

        if root is None:
            root = ''
        else:
            root = '%s/'%(root)
        if precision is None:
            precision = self.precision
        elif precision == 'double' and self.precision == 'single':
            raise ValueError("cannot cast single precision to double")
        outdtype = _real_dtypes[precision]
        group = '%scompressed_waveforms/%s' %(root, str(template_hash))
        for param in ['amplitude', 'phase', 'sample_points']:
            fp['%s/%s' %(group, param)] = self._get(param).astype(outdtype)
        fp_group = fp[group]
        fp_group.attrs['mismatch'] = self.mismatch
        fp_group.attrs['interpolation'] = self.interpolation
        fp_group.attrs['tolerance'] = self.tolerance
        fp_group.attrs['precision'] = precision