
import numpy as np
import math

from robots.posenode import PoseNode

class XYRobot(PoseNode):

    def __init__(self, **kwargs):
        self.motion_err = kwargs.pop('err', 0.)

        pose = np.array(kwargs.pop('pose', [0.,0.,0.]), dtype=float)
        super(XYRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's x-axis."""
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = np.abs(motion) * motion_err
        e = np.expand_dims(np.random.randn(2), 1)
        e *= sigma

        self.pose[0] += motion[0] + e[0]
        self.pose[1] += motion[1] + e[1]

class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):        
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0., 0.]), dtype=float)

        pose = np.array(kwargs.pop('pose', [0.,0.,0.]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma

        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi
        


51ffc5f9a4ad1879d3b7112e96b5b8a6117db9f2
<mask token>


class XYRobot(PoseNode):
    <mask token>
    <mask token>


class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0.0, 0.0]), dtype=float)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma
        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi

<mask token>


class XYRobot(PoseNode):
    <mask token>

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's x-axis."""
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = np.abs(motion) * motion_err
        e = np.expand_dims(np.random.randn(2), 1)
        e *= sigma
        self.pose[0] += motion[0] + e[0]
        self.pose[1] += motion[1] + e[1]


class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0.0, 0.0]), dtype=float)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma
        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi

<mask token>


class XYRobot(PoseNode):

    def __init__(self, **kwargs):
        self.motion_err = kwargs.pop('err', 0.0)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's x-axis."""
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = np.abs(motion) * motion_err
        e = np.expand_dims(np.random.randn(2), 1)
        e *= sigma
        self.pose[0] += motion[0] + e[0]
        self.pose[1] += motion[1] + e[1]


class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0.0, 0.0]), dtype=float)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma
        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi

import numpy as np
import math
from robots.posenode import PoseNode


class XYRobot(PoseNode):

    def __init__(self, **kwargs):
        self.motion_err = kwargs.pop('err', 0.0)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's x-axis."""
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = np.abs(motion) * motion_err
        e = np.expand_dims(np.random.randn(2), 1)
        e *= sigma
        self.pose[0] += motion[0] + e[0]
        self.pose[1] += motion[1] + e[1]


class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0.0, 0.0]), dtype=float)
        pose = np.array(kwargs.pop('pose', [0.0, 0.0, 0.0]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma
        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi


import numpy as np
import math

from robots.posenode import PoseNode

class XYRobot(PoseNode):

    def __init__(self, **kwargs):
        self.motion_err = kwargs.pop('err', 0.)

        pose = np.array(kwargs.pop('pose', [0.,0.,0.]), dtype=float)
        super(XYRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's x-axis."""
        motion_err = kwargs.pop('err', self.motion_err)
        sigma = np.abs(motion) * motion_err
        e = np.expand_dims(np.random.randn(2), 1)
        e *= sigma

        self.pose[0] += motion[0] + e[0]
        self.pose[1] += motion[1] + e[1]

class XYPhiRobot(PoseNode):
    """A robot fully described by its position in x,y and heading phi.

    Attributes
    ----------
    motion_err : 1x2 array
        The error associated with a single unit of motion (turn, drive).
    """

    def __init__(self, **kwargs):        
        """Create a XYPhiRobot.

        Kwargs
        ------
        err : 1x2 array, optional
            Array describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        pose : 1x3 array, optional
            1x3 pose vector. If omitted identity is assumed.
        """
        self.motion_err = np.array(kwargs.pop('err', [0., 0.]), dtype=float)

        pose = np.array(kwargs.pop('pose', [0.,0.,0.]), dtype=float)
        super(XYPhiRobot, self).__init__(pose=pose)

    def move(self, motion, **kwargs):
        """Move robot by first turning and then driving along the robot's new heading (x-axis).

        Params
        ------
        motion : 1x2 array
            Motion command [angle in radians, meter]        
              
        Kwargs
        ------
        err : 1x2 array, optional 
            Vector describing the error associated with motion. The error model assumes
            a zero centered normal distribution having a standard deviation proportional to
            [error per radians, error per meter].
        """
        motion_err = kwargs.pop('err', self.motion_err)
        
        sigma = motion_err * np.abs(motion)
        e = np.random.randn(2)
        e *= sigma

        phi = self.pose[2] + motion[0] + e[0]
        self.pose[0] += math.cos(phi) * (motion[1] + e[1])
        self.pose[1] += math.sin(phi) * (motion[1] + e[1])
        self.pose[2] = phi
        

