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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 bg_phase_mask_from_sim(sim, radial_clearance=1.1):
 """Return the background phase mask of a qpsphere simulation Parameters sim: qpimage.QPImage Quantitative phase data simulated with qpsphere; The simulation keyword arguments "sim center", "sim radius", and "pixel size" must be present in `sim.meta`. radial_clearance: float Multiplicator to the fitted radius of the sphere; modifies the size of the mask; set to "1" to use the radius determined by :func:`qpsphere.analyze`. The circular area containing the phase object is set to `False` in the output `mask` image. Returns ------- mask: boolean 2d np.ndarray The mask is `True` for background regions and `False` for object regions. """

    # Mask values around the object
    cx, cy = sim["sim center"]
    radius = sim["sim radius"]
    px_um = sim["pixel size"]
    x = np.arange(sim.shape[0]).reshape(-1, 1)
    y = np.arange(sim.shape[1]).reshape(1, -1)
    rsq = (x - cx)**2 + (y - cy)**2
    mask = rsq > (radius/px_um * radial_clearance)**2
    return mask