Usage examples and doc cleanup for Polynomial correction.

Refs #9574

Code/Mantid/docs/source/algorithms/PolynomialCorrection-v1.rst

@@ -10,14 +10,60 @@ Description
 -----------
 
 Corrects the data and error values on a workspace by the value of a
-polynomial function:
+polynomial function using the chosen operation. The correction factor is defined by
 
-.. math:: {\rm C0} + {\rm C1} x + {\rm C2} x^2 + ...
+.. math::
 
-which is evaluated at the *x* value of each data point (using the
-mid-point of the bin as the *x* value for histogram data. The data and
-error values are multiplied or divided by the value of this function.
-The order of the polynomial is determined by the length of the
-Coefficients property, which can be of any length.
+   C = \sum_{i}^{N} c_i x_i
+
+where *N* is the order of the polynomial specified by the length of the *Coefficients* property.
+The factor is evaluated at the *x* value of each data point (using the
+mid-point of the bin as the *x* value for histogram data.
+
+
+Usage
+-----
+
+**Example: divide data by a quadratic:**
+
+.. testcode::
+
+   # create histogram workspace
+   dataX = [0,1,2,3,4,5,6,7,8,9] # or use dataX=range(0,10)
+   dataY = [1,2,3,4,5,6,7,8,9]
+   dataE = [1,2,3,4,5,6,7,8,9]
+   data_ws = CreateWorkspace(dataX, dataY, DataE=dataE)
+
+   coefficients = [1., 3., 5.] #  1 + 3x + 5x^2
+   data_ws = PolynomialCorrection(data_ws, coefficients, Operation="Divide")
+
+   print "First 5 y values:", data_ws.readY(0)[0:5]
+   print "First 5 error values:", data_ws.readE(0)[0:5]
+
+.. testoutput::
+
+   First 5 y values: [ 0.26666667  0.11940299  0.0754717   0.05498282  0.04319654]
+   First 5 error values: [ 0.26666667  0.11940299  0.0754717   0.05498282  0.04319654]
+
+**Example: multiply data by a linear:**
+
+.. testcode::
+
+   # create histogram workspace
+   dataX = [0,1,2,3,4,5,6,7,8,9] # or use dataX=range(0,10)
+   dataY = [1,2,3,4,5,6,7,8,9]
+   dataE = [1,2,3,4,5,6,7,8,9]
+   data_ws = CreateWorkspace(dataX, dataY, DataE=dataE)
+
+   coefficients = [2., 4.] #  2 + 4x
+   data_ws = PolynomialCorrection(data_ws, coefficients, Operation="Multiply")
+
+   print "First 5 y values:", data_ws.readY(0)[0:5]
+   print "First 5 error values:", data_ws.readE(0)[0:5]
+
+.. testoutput::
+
+   First 5 y values: [   4.   16.   36.   64.  100.]
+   First 5 error values: [   4.   16.   36.   64.  100.]
 
 .. categories::