'**SUMMARY**
Scale the signal so the maximum and minimum values are
all scaled to the values in value_range. This is handy
if you want to compare the shape of two signals that
are scaled to different ranges.
**PARAMETERS**
* *value_range* - A tuple that provides the lower and upper bounds
for the output signal.
**RETURNS**
A scaled LineScan object.
**EXAMPLE**
>>>> import matplotlib.pyplot as plt
>>>> img = Image(\'lenna\')
>>>> sl = img.getLineScan(y=128)
>>>> plt.plot(sl)
>>>> plt.plot(sl.scale(value_range(0,255)))
>>>> plt.show()
**SEE ALSO**'

def scale(self, value_range=(0, 1)):

    temp = np.array(self, dtype='float32')
    vmax = np.max(temp)
    vmin = np.min(temp)
    a = np.min(value_range)
    b = np.max(value_range)
    temp = ((((b - a) / (vmax - vmin)) * (temp - vmin)) + a)
    retVal = LineScan(list(temp[:]), image=self.image, pointLoc=self.pointLoc, pt1=self.pt1, pt2=self.pt2)
    retVal._update(self)
    return retVal
