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A Closer Look at the Controls Class#

We have already seen in previous sections that once the problem has been defined in the project class, it is necessary to define a Controls object which, as its name suggests, tells RAT what we want to do with the project.

Making an instance of the Controls class is quite simple:

controls = controlsClass();

controls = RAT.Controls()

This then creates an instance of the Controls class with a number of options defined:

  controlsClass with properties:

            parallel: 'single'
           procedure: 'calculate'
    calcSldDuringFit: 0
             display: 'iter'
    resampleMinAngle: 0.9000
     resampleNPoints: 50

+------------------+-----------+
|     Property     |   Value   |
+------------------+-----------+
|    procedure     | calculate |
|     parallel     |   single  |
| calcSldDuringFit |   False   |
| resampleMinAngle |    0.9    |
| resampleNPoints  |     50    |
|     display      |    iter   |
+------------------+-----------+

We will look at each of these in more detail below. Note that the options that are visible depend on the procedure selected. So, at the moment the procedure is set to "calculate", which will simply calculate the reflectivity and SLD for any associated problem. If we select the "simplex" algorithm as the procedure, a different set of options appears:

controls.procedure = 'simplex';

controls.procedure = 'simplex'

  controlsClass with properties:

            parallel: 'single'
           procedure: 'simplex'
    calcSldDuringFit: 0
             display: 'iter'
          xTolerance: 1.0000e-06
       funcTolerance: 1.0000e-06
        maxFuncEvals: 10000
       maxIterations: 1000
          updateFreq: 1
      updatePlotFreq: 20
    resampleMinAngle: 0.9000
     resampleNPoints: 50

+------------------+---------+
|     Property     |  Value  |
+------------------+---------+
|    procedure     | simplex |
|     parallel     |  single |
| calcSldDuringFit |  False  |
| resampleMinAngle |   0.9   |
| resampleNPoints  |    50   |
|     display      |   iter  |
|    xTolerance    |  1e-06  |
|  funcTolerance   |  1e-06  |
|   maxFuncEvals   |  10000  |
|  maxIterations   |   1000  |
|    updateFreq    |    1    |
|  updatePlotFreq  |    20   |
+------------------+---------+

which allow the user to set things such as tolerance targets and so on. There are a different set of options for each algorithm. We will now look at each of the available options in turn.

General parameters for the Controls Class#

These are the general parameters for the controls class. For algorithm-specific parameters see the page for each algorithm in the algorithms section.

procedure#

Which algorithm RAT should run. Currently the options are:

parallel#

How the calculation should be parallelised. Currently the options are:

  • "single": do not parallelise.

  • "contrasts": each contrast gets its own calculation thread.

  • "points": each contrast is split into a number of sections, and each section gets its own calculation thread.

Which option is more efficient will depend on the number of contrasts and the size of your data.

calcSldDuringFit#

A boolean (true or false) value which determines whether SLD will be calculated during the fit (for live plotting etc.)

display#

How much RAT should print to the terminal. The current options are:

  • "off": No display.

  • "iter": Give information after every iteration for iterative algorithms.

  • "notify":

  • "final": Just provide information when the calculation has finished.

Resampling parameters (resampleMinAngle and resampleNPoints)#

The two parameters resampleMinAngle and resampleNPoints decide how adaptive resampling will be used on the SLD profiles. See the resampling page for more details. In short:

  • resampleMinAngle: For each data point, the algorithm draws two lines from that data point to its neighbouring points on either side. If the angle between those lines is smaller than resampleMinAngle, then the algorithm will refine over that point.

    In practice, this means that resampling happens for points which are significantly higher or lower than their neighbours (i.e. the gradient of the function has changed rapidly) and resampleMinAngle controls the sensitivity of this.

    resampleMinAngle is defined in the units of “radians divided by pi”, i.e. resampleMinAngle = 0.9 refines where the adjacent points form an angle smaller than \(0.9 \pi\) radians.

  • resampleNPoints: The initial number of domain points (layers) sampled by the algorithm at the start.

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