VectorDimensionalityReduction - Vector Dimensionality Reduction

Performs dimensionality reduction of the input vector data according to a model file.

Detailed description

This application performs a vector data dimensionality reduction based on a model file produced by the TrainDimensionalityReduction application.


This section describes in details the parameters available for this application. Table [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is VectorDimensionalityReduction .

[1]Table: Parameters table for Vector Dimensionality Reduction.
Parameter Key Parameter Name Parameter Type
in Name of the input vector data Input vector data
instat Statistics file Input File name
model Model file Input File name
out Output vector data file containing the reduced vector Output File name
feat Input features to use for reduction. List
featout Output feature Choices
featout prefix Prefix Choice
featout list List Choice Feature name prefix String
featout.list.names Feature name list String list
pcadim Principal component dimension Int
mode Writing mode Choices
mode overwrite Overwrite Choice
mode update Update Choice
inxml Load otb application from xml file XML input parameters file
outxml Save otb application to xml file XML output parameters file

Name of the input vector data: The input vector data to reduce.

Statistics file: A XML file containing mean and standard deviation to center and reduce samples before dimensionality reduction (produced by ComputeImagesStatistics application).

Model file: A model file (produced by the TrainDimensionalityReduction application,.

Output vector data file containing the reduced vector: Output vector data file storing sample values (OGR format). If not given, the input vector data file is used. In overwrite mode, the original features will be lost.

Input features to use for reduction.: List of field names in the input vector data used as features for reduction.

Output feature: Naming of output features. Available choices are:

  • Prefix: Use a name prefix.
  • Feature name prefix: Name prefix for output features. This prefix is followed by the numeric index of each output feature.
  • List: Use a list with all names.
  • Feature name list: List of field names for the output features which result from the reduction.

Principal component dimension: This optional parameter can be set to reduce the number of eignevectors used in the PCA model file. This parameter can’t be used for other models.

Writing mode: This parameter determines if the output file is overwritten or updated [overwrite/update]. If an output file name is given, the original file is copied before creating the new features. Available choices are:

  • Overwrite: Overwrite mode.
  • Update: Update mode.

Load otb application from xml file: Load otb application from xml file.

Save otb application to xml file: Save otb application to xml file.


To run this example in command-line, use the following:

otbcli_VectorDimensionalityReduction -in vectorData.shp -instat meanVar.xml -model model.txt -out vectorDataOut.shp -feat perimeter area width

To run this example from Python, use the following code snippet:


# Import the otb applications package
import otbApplication

# The following line creates an instance of the VectorDimensionalityReduction application
VectorDimensionalityReduction = otbApplication.Registry.CreateApplication("VectorDimensionalityReduction")

# The following lines set all the application parameters:
VectorDimensionalityReduction.SetParameterString("in", "vectorData.shp")

VectorDimensionalityReduction.SetParameterString("instat", "meanVar.xml")

VectorDimensionalityReduction.SetParameterString("model", "model.txt")

VectorDimensionalityReduction.SetParameterString("out", "vectorDataOut.shp")

# The following line execute the application




This application has been written by OTB-Team.

See Also

These additional resources can be useful for further information: