Exemplo n.º 1
0
    def simple_mamdani():
        fe = Engine('simple-mamdani')
        energy = InputVariable('Energy')
        energy.term['LOW'] = Triangle('LOW', 0.0, 0.5, 1.0)
        energy.term['MEDIUM'] = Triangle('MEDIUM', 0.5, 1.0, 1.5)
        energy.term['HIGH'] = Triangle('HIGH', 1.0, 1.5, 2.0)
        fe.input['Energy'] = energy

        health = OutputVariable('Health', default=float('nan'))
        health.term['BAD'] = LeftShoulder('BAD', 0.0, 0.5)
        health.term['REGULAR'] = Triangle('REGULAR', 0.5, 1.0, 1.5)
        health.term['GOOD'] = RightShoulder('GOOD', 1.0, 1.5)
        fe.output['Health'] = health

        ruleblock = RuleBlock()
        ruleblock.append(
            MamdaniRule.parse('if Energy is LOW then Health is BAD', fe))
        ruleblock.append(
            MamdaniRule.parse('if Energy is MEDIUM then Health is REGULAR',
                              fe))
        ruleblock.append(
            MamdaniRule.parse('if Energy is HIGH then Health is GOOD', fe))
        fe.ruleblock[ruleblock.name] = ruleblock

        fe.configure(Operator())
        return fe
Exemplo n.º 2
0
 def process_output_vars(self, block):
     if len(block) <= 1:
         raise SyntaxError('expected at least one variable in %s' % block)
     for variable in block[1:]:
         token = variable.split(':')
         if len(token) != 2:
             raise SyntaxError('malformed property <%s>' % variable)
         name = token[0]
         self.fe.output[name] = OutputVariable(name)
Exemplo n.º 3
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 def simple_mamdani():
     fe = Engine('simple-mamdani')
     energy = InputVariable('Energy')
     energy.term['LOW'] = Triangle('LOW', 0.0, 0.5, 1.0)
     energy.term['MEDIUM'] = Triangle('MEDIUM', 0.5, 1.0, 1.5)
     energy.term['HIGH'] = Triangle('HIGH', 1.0, 1.5, 2.0)
     fe.input['Energy'] = energy
     
     health = OutputVariable('Health', default=float('nan'))
     health.term['BAD'] = LeftShoulder('BAD', 0.0, 0.5)
     health.term['REGULAR'] = Triangle('REGULAR', 0.5, 1.0, 1.5)
     health.term['GOOD'] = RightShoulder('GOOD', 1.0, 1.5)
     fe.output['Health'] = health
     
     ruleblock = RuleBlock()
     ruleblock.append(MamdaniRule.parse('if Energy is LOW then Health is BAD', fe))
     ruleblock.append(MamdaniRule.parse('if Energy is MEDIUM then Health is REGULAR', fe))
     ruleblock.append(MamdaniRule.parse('if Energy is HIGH then Health is GOOD', fe))
     fe.ruleblock[ruleblock.name] = ruleblock
     
     fe.configure(Operator())
     return fe
Exemplo n.º 4
0
def simple_ai_boat():
    fe = Engine('simple-mamdani')
    """
        RELATIVE LOCATION

        ----------\    X       X      X       ------------
                   \  / \     / \    / \     /
                    \/   \   /   \  /   \   /   
                    /\    \ /     \/     \ /     
                   /  \    X      /\      X       
                  /    \  / \    /  \    / \       

         FAR        BEHIND           AHEAD       FAR
         BEHIND              ABOUT               AHEAD
                             EVEN
        """

    #shoulder break points in meters
    FAR_MAX = 85.0
    FAR_MIN = 60.0

    #behind/ahead points in meters
    BEHIND_AHEAD_MIN = 66.0
    BEHIND_AHEAD_MIDPOINT = 40.0
    BEHIND_AHEAD_MAX = 14.0

    # about even magnitude - triangle membership
    ABOUT_EVEN_MAGNITUDE = 16.0

    relative_location = InputVariable('relative_location')
    relative_location.term['FAR_BEHIND'] = LeftShoulder(
        'FAR_BEHIND', -FAR_MAX, -FAR_MIN)
    relative_location.term['BEHIND'] = Triangle('BEHIND', -BEHIND_AHEAD_MIN,
                                                -BEHIND_AHEAD_MIDPOINT,
                                                -BEHIND_AHEAD_MAX)
    relative_location.term['ABOUT_EVEN'] = Triangle('ABOUT_EVEN',
                                                    -ABOUT_EVEN_MAGNITUDE, 0.0,
                                                    ABOUT_EVEN_MAGNITUDE)
    relative_location.term['AHEAD'] = Triangle('AHEAD', BEHIND_AHEAD_MAX,
                                               BEHIND_AHEAD_MIDPOINT,
                                               BEHIND_AHEAD_MIN)
    relative_location.term['FAR_AHEAD'] = RightShoulder(
        'FAR_AHEAD', FAR_MIN, FAR_MAX)
    fe.input['relative_location'] = relative_location

    # locations in a 2000 m piece in meters
    location = InputVariable('location')
    location.term['BEGINNING'] = LeftShoulder('BEGINNING', 500.0, 800.0)
    location.term['MIDDLE'] = Trapezoid('MIDDLE', 650.0, 800.0, 1500.0, 1600.0)
    location.term['END'] = RightShoulder('END', 1570.0, 1700.0)
    fe.input['location'] = location
    """
        ACTION:


        ------------\ ---------\ ----------------\  -------\  ---------
                     X          X                 \/        \/
                    / \        / \                /\        /\ 
         EASE_UP   /   \ AS   /   \    LENGTHEN  /  \ P10  /  \ SPRINT
                         IS
        """

    # ACTION values are unit-less

    EASE_UP_MIN = 20.0
    EASE_UP_MAX = 25.0

    AS_IS_MIN = 20.0
    AS_IS_B = 35.0
    AS_IS_C = 70.0
    AS_IS_MAX = 75.0

    LENGTHEN_MIN = 70.0
    LENGTHEN_B = 73.0
    LENGTHEN_C = 77.0
    LENGTHEN_MAX = 80.0

    P10_MIN = 77.0
    P10_B = 80.0
    P10_C = 90.0
    P10_MAX = 93.0

    SPRINT_MIN = 90.0
    SPRINT_MAX = 95.0

    action = OutputVariable('action', default=float('nan'))
    action.term['EASE_UP'] = LeftShoulder('EASE_UP', EASE_UP_MIN, EASE_UP_MAX)
    action.term['AS_IS'] = Trapezoid('AS_IS', AS_IS_MIN, AS_IS_B, AS_IS_C,
                                     AS_IS_MAX)
    action.term['LENGTHEN'] = Trapezoid('LENGTHEN', LENGTHEN_MIN, LENGTHEN_B,
                                        LENGTHEN_C, LENGTHEN_MAX)
    action.term['P10'] = Trapezoid('P10', P10_MIN, P10_B, P10_C, P10_MAX)
    action.term['SPRINT'] = RightShoulder('SPRINT', SPRINT_MIN, SPRINT_MAX)
    fe.output['action'] = action

    ruleblock = RuleBlock()

    ruleblock.append(
        MamdaniRule.parse('if location is BEGINNING then action is AS_IS', fe))

    ruleblock.append(
        MamdaniRule.parse(
            'if location is MIDDLE and relative_location is FAR_BEHIND then action is LENGTHEN',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is MIDDLE and relative_location is BEHIND then action is P10',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is MIDDLE and relative_location is ABOUT_EVEN then action is P10',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is MIDDLE and relative_location is AHEAD then action is LENGTHEN',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is MIDDLE and relative_location is FAR_AHEAD then action is AS_IS',
            fe))

    ruleblock.append(
        MamdaniRule.parse(
            'if location is END and relative_location is FAR_BEHIND then action is LENGTHEN',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is END and relative_location is BEHIND then action is SPRINT',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is END and relative_location is ABOUT_EVEN then action is SPRINT',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is END and relative_location is AHEAD then action is SPRINT',
            fe))
    ruleblock.append(
        MamdaniRule.parse(
            'if location is END and relative_location is FAR_AHEAD then action is AS_IS',
            fe))

    fe.ruleblock[ruleblock.name] = ruleblock

    fe.configure(Operator())
    return fe