diff --git a/docs/source/algorithms/ScaleX-v1.rst b/docs/source/algorithms/ScaleX-v1.rst
index 26ed1ca5760c8ec2e4835c6de086d62057a956c1..443e864f69d7fd363d1359d3ad42d90ca915adbd 100644
--- a/docs/source/algorithms/ScaleX-v1.rst
+++ b/docs/source/algorithms/ScaleX-v1.rst
@@ -36,12 +36,12 @@ Usage
 
     # Center the Gaussian by shifting the X-axis, then find its average
     ws2 = ScaleX(ws, Factor=-mean, Operation='Add')
-    print 'mean=%.2f'%abs(np.sum( ws2.dataX(0) *ws2.dataY(0) ) / np.sum( ws2.dataY(0) ))
+    print('mean={:.2f}'.format(abs(np.sum( ws2.dataX(0) *ws2.dataY(0) ) / np.sum( ws2.dataY(0) ))))
 
     # Decrease the standard deviation of the Gaussian by half via shrinkage of the X-axis,
     # then find its standard deviation
     ws3 = ScaleX(ws2, Factor=0.5, Operation='Multiply')
-    print 'sigma=%.2f'%np.sqrt( np.sum( ws3.dataX(0)**2 *ws3.dataY(0) ) / np.sum( ws3.dataY(0) ) )
+    print('sigma={:.2f}'.format(np.sqrt( np.sum( ws3.dataX(0)**2 *ws3.dataY(0) ) / np.sum( ws3.dataY(0) ) )))
 
 Output: