Makes a simple plot of signal

        :param fig: (optional)
            Argument for :func:`plotutils.setfig`.

        :param plot_trap: (optional)
            Whether to plot the (best-fit least-sq) trapezoid fit.

        :param name: (optional)
            Whether to annotate plot with the name of the signal;
            can be ``True`` (in which case ``self.name`` will be
            used), or any arbitrary string.

        :param trap_color: (optional)
            Color of trapezoid fit line.

        :param trap_kwargs: (optional)
            Keyword arguments to pass to trapezoid fit line.

        :param **kwargs: (optional)
            Additional keyword arguments passed to ``plt.plot``.

def plot(self, fig=None, plot_trap=False, name=False, trap_color='g',
             trap_kwargs=None, **kwargs):
        """
        Makes a simple plot of signal

        :param fig: (optional)
            Argument for :func:`plotutils.setfig`.

        :param plot_trap: (optional)
            Whether to plot the (best-fit least-sq) trapezoid fit.

        :param name: (optional)
            Whether to annotate plot with the name of the signal;
            can be ``True`` (in which case ``self.name`` will be
            used), or any arbitrary string.

        :param trap_color: (optional)
            Color of trapezoid fit line.

        :param trap_kwargs: (optional)
            Keyword arguments to pass to trapezoid fit line.

        :param **kwargs: (optional)
            Additional keyword arguments passed to ``plt.plot``.


        """

        setfig(fig)

        plt.plot(self.ts,self.fs,'.',**kwargs)

        if plot_trap and hasattr(self,'trapfit'):
            if trap_kwargs is None:
                trap_kwargs = {}
            plt.plot(self.ts, traptransit(self.ts,self.trapfit),
                     color=trap_color, **trap_kwargs)

        if name is not None:
            if type(name)==type(''):
                text = name
            else:
                text = self.name
            plt.annotate(text,xy=(0.1,0.1),xycoords='axes fraction',fontsize=22)

        if hasattr(self,'depthfit') and not np.isnan(self.depthfit[0]):
            lo = 1 - 3*self.depthfit[0]
            hi = 1 + 2*self.depthfit[0]
        else:
            lo = 1
            hi = 1

        sig = qstd(self.fs,0.005)
        hi = max(hi,self.fs.mean() + 7*sig)
        lo = min(lo,self.fs.mean() - 7*sig)
        logging.debug('lo={}, hi={}'.format(lo,hi))
        plt.ylim((lo,hi))
        plt.xlabel('time [days]')
        plt.ylabel('Relative flux')