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Usage
All statistics algorithms can conceptually be operated with
several options: Learn: given an input data set, calculate a
minimal statistical model (e.g., sums, raw moments, joint
probabilities). Derive: given an input minimal statistical
model, derive the full model (e.g., descriptive statistics,
quantiles, correlations, conditional probabilities). NB: It
may be, or not be, a problem that a full model was not
derived. For instance, when doing parallel calculations, one
only wants to derive the full model after all partial
calculations have completed. On the other hand, one can also
directly provide a full model, that was previously
calculated or guessed, and not derive a new one. Assess:
given an input data set, input statistics, and some form of
threshold, assess a subset of the data set. Test: perform at
least one statistical test. Therefore, a
vtkStatisticsAlgorithm has the following vtkTable ports 3
input ports: Data (mandatory) Parameters to the learn phase
(optional) Input model (optional) 3 output port (called
Output): Data (annotated with assessments when the Assess
option is ON). Output model (identical to the the input
model when Learn option is OFF). Meta information about the
model and/or the overall fit of the data to the model; is
filled only when the Assess option is ON.
.SECTION Thanks Thanks to Philippe Pebay and David Thompson
from Sandia National Laboratories for implementing this
class.
To create an instance of class vtkStatisticsAlgorithm,
simply invoke its constructor as follows
obj = vtkStatisticsAlgorithm
Methods
The class vtkStatisticsAlgorithm has several methods that
can be used. They are listed below. Note that the
documentation is translated automatically from the VTK
sources, and may not be completely intelligible. When in
doubt, consult the VTK website. In the methods listed below,
obj is an instance of the vtkStatisticsAlgorithm class.
* string = obj.GetClassName ()
* int = obj.IsA (string name)
* vtkStatisticsAlgorithm = obj.NewInstance ()
* vtkStatisticsAlgorithm = obj.SafeDownCast (vtkObject o)
* obj.SetLearnOptionParameterConnection (vtkAlgorithmOutput
params) - A convenience method for setting learn input
parameters (if one is expected or allowed). It is
equivalent to calling SetInput( 1, params );
* obj.SetLearnOptionParameters (vtkDataObject params) - A
convenience method for setting the input model (if one is
expected or allowed). It is equivalent to calling
SetInputConnection( 2, model );
* obj.SetInputModelConnection (vtkAlgorithmOutput model) - /
/ obj.SetInputModel (vtkDataObject model) - Set/Get the
Learn option.
* obj.SetLearnOption (bool ) - Set/Get the Learn option.
* bool = obj.GetLearnOption () - Set/Get the Learn option.
* obj.SetDeriveOption (bool ) - Set/Get the Derive option.
* bool = obj.GetDeriveOption () - Set/Get the Derive option.
* obj.SetAssessOption (bool ) - Set/Get the Assess option.
* bool = obj.GetAssessOption () - Set/Get the Assess option.
* obj.SetTestOption (bool ) - Set/Get the Test option.
* bool = obj.GetTestOption () - Set/Get the Test option.
* obj.SetAssessParameters (vtkStringArray ) - Set/get
assessment parameters.
* vtkStringArray = obj.GetAssessParameters () - Set/get
assessment parameters.
* obj.SetAssessNames (vtkStringArray ) - Set/get assessment
names.
* vtkStringArray = obj.GetAssessNames () - Set/get
assessment names.
* obj.SetColumnStatus (string namCol, int status) - Add or
remove a column from the current analysis request. Once
all the column status values are set, call
RequestSelectedColumns() before selecting another set of
columns for a different analysis request. The way that
columns selections are used varies from algorithm to
algorithm.
Note: the set of selected columns is maintained in
vtkStatisticsAlgorithmPrivate::Buffer until
RequestSelectedColumns() is called, at which point the set
is appended to vtkStatisticsAlgorithmPrivate::Requests. If
there are any columns in vtkStatisticsAlgorithmPrivate::
Buffer at the time RequestData() is called,
RequestSelectedColumns() will be called and the selection
added to the list of requests.
* obj.ResetAllColumnStates () - Set the the status of each
and every column in the current request to OFF (0).
* int = obj.RequestSelectedColumns () - Use the current
column status values to produce a new request for
statistics to be produced when RequestData() is called.
See SetColumnStatus() for more information.
* obj.ResetRequests () - Empty the list of current requests.
* vtkIdType = obj.GetNumberOfRequests () - Return the number
of requests. This does not include any request that is in
the column-status buffer but for which
RequestSelectedColumns() has not yet been called (even
though it is possible this request will be honored when
the filter is run – see SetColumnStatus() for more
information).
* vtkIdType = obj.GetNumberOfColumnsForRequest (vtkIdType
request) - Return the number of columns for a given
request.
* string = obj.GetColumnForRequest (vtkIdType r, vtkIdType
c) - Provide the name of the c-th column for the r-th
request.
For the version of this routine that returns an integer,
if the request or column does not exist because r or c is
out of bounds, this routine returns 0 and the value of
columnName is unspecified. Otherwise, it returns 1 and the
value of columnName is set.
For the version of this routine that returns const char*,
if the request or column does not exist because r or c is
out of bounds, the routine returns NULL. Otherwise it
returns the column name. This version is not thread-safe.
* obj.Aggregate (vtkDataObjectCollection , vtkDataObject ) -
Given a collection of models, calculate aggregate model
* FreeMat_Documentation
* Visualization_Toolkit_Infovis_Classes
* Generated on Thu Jul 25 2013 17:18:34 for FreeMat by
doxygen_ 1.8.1.1
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