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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 plot(self):
 """ Quick visualization of calibration solution. """

        import pylab as p
        p.clf()
        fig = p.figure(1)
        nspw = len(self.gain[0])
        ext = n.ceil(n.sqrt(nspw))  # find best squre plot (simplest)
        for spw in range(len(self.gain[0])):
            ax = fig.add_subplot(ext, ext, spw+1)
            for pol in [0,1]:
                ax.scatter(range(len(self.gain)), n.abs(self.gain.data[:,spw,pol]), color=n.array(['k','y']).take(self.gain.mask[:,spw,pol]), marker=['x','.'][pol])

        fig.show()