Parametric Models
Outliers
Specify outliers using the class type:
class_type = "outliers"
Outliers are sampled from the 2D space defined by \(x_r \times y_r\), where \(x_r\) (x range) is the closed interval of values that x can take and \(y_r\) (y range) is the closed interval of values that y can take.
"outliers": {
"x_r": (-2.5, 2.5),
"y_r": (-2.5, 2.5)
}
Conics
Circles
Specify circles using the class type:
class_type = "circles"
Circles are generated by uniformly sampling a center and a radius from the closed intervals specified by the user.
The default values are:
"circles": {
"radius_r": (0.5, 1.5),
"x_center_r": (-1.0, 1.0),
"y_center_r": (-1.0, 1.0),
}
Lines
Specify lines using the class type:
class_type = "lines"
Lines are generated by randomly sampling two points in the 2D space \(x_r \times y_r\) to define slope and intercept, and then sampling points belonging to this line. Each point of the line is ensured to belong to the 2D space \(x_r \times y_r\).
"lines": {
"x_r": (-2.5, 2.5),
"y_r": (-2.5, 2.5)
}
Ellipses
Specify ellipses using the class type:
class_type = "ellipses"
Ellipses are generated by uniformly sampling a center and a radius from the closed intervals specified by the user, and then applying horizontal stretch/shrinkage to the sampled circle.
The default values are:
"ellipses": {
"radius_r": (0.5, 1.5),
"x_center_r": (-1, 1),
"y_center_r": (-1, 1),
"width_r": (0.1, 1),
"height_r": (0.1, 1)
}
Any Conic
Specify any conic using the class type:
class_type = "conics"
This option randomly samples models from all the classes specified above. Note: Hyperbola is not implemented yet.