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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 from_lasio_curve(cls, curve, depth=None, basis=None, start=None, stop=None, step=0.1524, run=-1, null=-999.25, service_company=None, date=None):
 """ Makes a curve object from a lasio curve object and either a depth basis or start and step information. Args: curve (ndarray) depth (ndarray) basis (ndarray) start (float) stop (float) step (float):
 default: 0.1524 run (int):
 default: -1 null (float):
 default: -999.25 service_company (str):
 Optional. data (str):
 Optional. Returns: Curve. An instance of the class. """

        data = curve.data
        unit = curve.unit

        # See if we have uneven sampling.
        if depth is not None:
            d = np.diff(depth)
            if not np.allclose(d - np.mean(d), np.zeros_like(d)):
                # Sampling is uneven.
                m = "Irregular sampling in depth is not supported. "
                m += "Interpolating to regular basis."
                warnings.warn(m)
                step = np.nanmedian(d)
                start, stop = depth[0], depth[-1]+0.00001  # adjustment
                basis = np.arange(start, stop, step)
                data = np.interp(basis, depth, data)
            else:
                step = np.nanmedian(d)
                start = depth[0]

        # Carry on with easier situations.
        if start is None:
            if basis is not None:
                start = basis[0]
                step = basis[1] - basis[0]
            else:
                raise CurveError("You must provide a basis or a start depth.")

        if step == 0:
            if stop is None:
                raise CurveError("You must provide a step or a stop depth.")
            else:
                step = (stop - start) / (curve.data.shape[0] - 1)

        # Interpolate into this.

        params = {}
        params['mnemonic'] = curve.mnemonic
        params['description'] = curve.descr
        params['start'] = start
        params['step'] = step
        params['units'] = unit
        params['run'] = run
        params['null'] = null
        params['service_company'] = service_company
        params['date'] = date
        params['code'] = curve.API_code

        return cls(data, params=params)