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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 almost_equal_elem(self,other,tol,relative=True,dtol=0.0):
 """ Compare whether two time series are almost equal, element by element. If the 'relative' parameter is 'True' (the default) then the 'tol' parameter (which must be positive) is interpreted as a relative tolerance, and the comparison returns 'True' only if abs(self[i]-other[i]) <= tol*abs(self[i]) for all elements of the series. If 'relative' is 'False', then 'tol' is an absolute tolerance, and the comparison is true only if abs(self[i]-other[i]) <= tol for all elements of the series. The method also checks that self.delta_t is within 'dtol' of other.delta_t; if 'dtol' has its default value of 0 then exact equality between the two is required. Other meta-data (type, dtype, length, and epoch) must be exactly equal. If either object's memory lives on the GPU it will be copied to the CPU for the comparison, which may be slow. But the original object itself will not have its memory relocated nor scheme changed. Parameters other: another Python object, that should be tested for almost-equality with 'self', element-by-element. tol: a non-negative number, the tolerance, which is interpreted as either a relative tolerance (the default) or an absolute tolerance. relative: A boolean, indicating whether 'tol' should be interpreted as a relative tolerance (if True, the default if this argument is omitted) or as an absolute tolerance (if tol is False). dtol: a non-negative number, the tolerance for delta_t. Like 'tol', it is interpreted as relative or absolute based on the value of 'relative'. This parameter defaults to zero, enforcing exact equality between the delta_t values of the two TimeSeries. Returns ------- boolean: 'True' if the data and delta_ts agree within the tolerance, as interpreted by the 'relative' keyword, and if the types, lengths, dtypes, and epochs are exactly the same. """

        # Check that the delta_t tolerance is non-negative; raise an exception
        # if needed.
        if (dtol < 0.0):
            raise ValueError("Tolerance in delta_t cannot be negative")
        if super(TimeSeries,self).almost_equal_elem(other,tol=tol,relative=relative):
            if relative:
                return (self._epoch == other._epoch and
                        abs(self._delta_t-other._delta_t) <= dtol*self._delta_t)
            else:
                return (self._epoch == other._epoch and
                        abs(self._delta_t-other._delta_t) <= dtol)
        else:
            return False