Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
Function | InOut | Function | Mandatory | Parameters defining the fitting function and its initial values |
InputWorkspace | Input | Workspace | Mandatory | Name of the input Workspace |
IgnoreInvalidData | Input | boolean | False | Flag to ignore infinities, NaNs and data with zero errors. |
DomainType | Input | string | Simple | The type of function domain to use: Simple, Sequential, or Parallel. Allowed values: [‘Simple’, ‘Sequential’, ‘Parallel’] |
EvaluationType | Input | string | CentrePoint | The way the function is evaluated on histogram data sets. If value is “CentrePoint” then function is evaluated at centre of each bin. If it is “Histogram” then function is integrated within the bin and the integrals returned. Allowed values: [‘CentrePoint’, ‘Histogram’] |
OutputWorkspace | Output | Workspace | Mandatory | An output workspace. |
The algorithm will use the axes of the input workspace to evaluate a functions on them and store the result in the output workspace.
Example - 1D function and a matrix workspace.
# Load a workspace
ws = Load('MUSR00015189')
# Evaluate a function
EvaluateFunction('name=ExpDecay,Height=56', 'ws_1', StartX=0, EndX=30, OutputWorkspace='out')
Example - 2D function and a MD workspace.
# Create an empty 2D workspace (100 x 100)
nx = 100
ny = 100
ws = CreateMDHistoWorkspace(Dimensionality=2, Extents=[-10,10,-10,10], Names="x,y", Units="U,V",
NumberOfBins='%s,%s' % (nx,ny),
SignalInput=[0] * nx * ny, ErrorInput=[0] * nx * ny)
# Evaluate a function
EvaluateFunction('name=UserFunctionMD,Formula=sin(x)*sin(y)','ws', OutputWorkspace='out')
Categories: Algorithms | Optimization