John W. Campbell
This class stores the multiples (+singles) data for a Laue multiple
set of harmonics and then tests to see whether individual reflections can be
potentially deconvoluted from these based on the data given and a given
wavelength normalisation curve.
Class, constructors and methods:
Class Details
Accessible Fields
Constructor
- Package:
- Jdl.JdlPX;
- Class name:
- JdlLaueDeconvPredictor
- Class definition:
- public class JdlLaueDeconvPredictor
- Extends:
- Object
- Implements:
- none
- Actions:
- none
The following accessible fields have been defined:
- Vector<Equation> equations
- boolean predicted_data
- int nh
- int nk
- int nl
- int maxharm_found
A single constructor is available to set up the 'empty' object. This
object may be re-used as often as required by invoking the clear() method
between each set of harmonics being investigated.
Constructors:
Default Constructor
Clear object - clear
Add spot - addSpot
Predict deconvolution - predictDeconvolution
This constructs a JdlLaueDeconvPredictor object with an initial
capacity for 20 spot measurements to be incremented in blocks of 20 spots
as required.
- Constructor Definition:
- public JdlLaueDeconvPredictor()
- Parameters List:
- none
This method clears the stored spots list in preparation for another
deconvolution test.
- Method Definition:
- public void clear()
- Parameters List:
- none
This method is used to add the spots data for the current set of harmonics
whose deconvolution is to be investigated.
- Method Definition:
- public boolean addSpot(JdlPredictedLaueSpot spot)
- Parameters List:
- spot
- The spot data to be added.
- Method Return:
-
true if spot added OK, false if harmonic does not belong to the
set of harmonics currently being processed (i.e. not the same nodal indices).
After the required spots have been added, this method may be called to
test the potential deconvolution of individual reflections from the
multiple (and possibly also single) spots. If successful, a vector of
'deconvoluted' reflections will be returned.
- Method Definition:
- public Vector predictDeconvolution(JdlChebyshevPolynomial curv, double scal_max, JdlError err)
- Parameters List:
- curv
- The wavelength normalisation curve to be used in the
deconvolution test. A curve generated by the testLambdaCurve(..) method
of the JdlTestLambdaCurve object may, for example, be used.
- scal_max
- A maximum scale factor (derived from the wavelength
normalisation curve) to be used e.g. 25.0.
- err
- Error return flag. If an error was found, err.err will be
returned as true (for flag values up to 3), a message will be returned
in err.msg1 and the flag err.flag will be set as follows:
= -1, No spots defined for deconvolution test
= 1, No suitable spots for deconvolution test
= 2, No valid deconvolution equations found
= 3, No singles or deconvoluted multiples
= 4, Insufficient equations to deconvolute multiples
= 5, Matrix cannot be inverted </br>
- Method Return:
-
A vector of deconvoluted spots (JdlPredictedLaueSpot objects).
(may be null if err.err was set to true - see above).
⇑ Up 2
⇑ Up 1
⇑ Top of this