#! /usr/bin/env python

from dynamic_reconfigure.parameter_generator_catkin import int_t
from dynamic_reconfigure.parameter_generator_catkin import double_t
from dynamic_reconfigure.parameter_generator_catkin import bool_t
from dynamic_reconfigure.parameter_generator_catkin import str_t

# set up parameters that we care about
PACKAGE = 'pcl_ros'


def add_common_parameters(gen):
    # add(self, name, paramtype, level, description, default = None, min = None,
    # max = None, edit_method = "")
    gen.add("max_iterations", int_t, 0,
            "The maximum number of iterations the algorithm will run for",
            50, 0, 100000)
    gen.add("probability", double_t, 0,
            "The desired probability of choosing at least one sample free from outliers",
            0.99, 0.5, 0.99)
    gen.add("distance_threshold", double_t, 0,
            "The distance to model threshold",
            0.02, 0, 1.0)
    gen.add("optimize_coefficients", bool_t, 0,
            "Model coefficient refinement",
            True)
    gen.add("radius_min", double_t, 0,
            "The minimum allowed model radius (where applicable)",
            0.0, 0, 1.0)
    gen.add("radius_max", double_t, 0,
            "The maximum allowed model radius (where applicable)",
            0.05, 0, 1.0)
    gen.add("eps_angle", double_t, 0,
            ("The maximum allowed difference between the model normal "
             "and the given axis in radians."),
            0.17, 0.0, 1.5707)
    gen.add("min_inliers", int_t, 0,
            "The minimum number of inliers a model must have in order to be considered valid.",
            0, 0, 100000)
    gen.add("input_frame", str_t, 0,
            ("The input TF frame the data should be transformed into, "
             "if input.header.frame_id is different."),
            "")
    gen.add("output_frame", str_t, 0,
            ("The output TF frame the data should be transformed into, "
             "if input.header.frame_id is different."),
            "")