Class GridParameters
- Namespace
- Bonsai.ML.LinearDynamicalSystems.LinearRegression
- Assembly
- Bonsai.ML.LinearDynamicalSystems.dll
Represents an operator that creates the 2D grid parameters used for calculating the PDF of a multivariate distribution.
[Combinator]
[WorkflowElementCategory(ElementCategory.Source)]
public class GridParameters
- Inheritance
-
GridParameters
- Inherited Members
Properties
X0
Gets or sets the lower bound of the X axis.
[JsonProperty("x0")]
public double X0 { get; set; }
Property Value
X1
Gets or sets the upper bound of the X axis.
[JsonProperty("x1")]
public double X1 { get; set; }
Property Value
XSteps
Gets or sets the number of steps along the X axis.
[JsonProperty("xsteps")]
public int XSteps { get; set; }
Property Value
Y0
Gets or sets the lower bound of the Y axis.
[JsonProperty("y0")]
public double Y0 { get; set; }
Property Value
Y1
Gets or sets the upper bound of the Y axis.
[JsonProperty("y1")]
public double Y1 { get; set; }
Property Value
YSteps
Gets or sets the number of steps along the Y axis.
[JsonProperty("ysteps")]
public int YSteps { get; set; }
Property Value
Methods
ConvertPyObject(PyObject)
Converts a PyObject, represeting a Kalman Filter Linear Regression Model, into a GridParameters object
public static GridParameters ConvertPyObject(PyObject pyObject)
Parameters
pyObjectPyObject
Returns
Process()
Generates grid parameters
public IObservable<GridParameters> Process()
Returns
Process(IObservable<PyObject>)
Gets the grid parameters from a PyObject of a Kalman Filter Linear Regression Model
public IObservable<GridParameters> Process(IObservable<PyObject> source)
Parameters
sourceIObservable<PyObject>
Returns
Process<TSource>(IObservable<TSource>)
Generates grid parameters on each input
public IObservable<GridParameters> Process<TSource>(IObservable<TSource> source)
Parameters
sourceIObservable<TSource>
Returns
Type Parameters
TSource
ToString()
Returns a string that represents the current object.
public override string ToString()
Returns
- string
A string that represents the current object.