import unittest
import kivy.multistroke
from kivy.multistroke import Recognizer, MultistrokeGesture
from kivy.vector import Vector

best_score = 0.0
counter = 0


def best_score_cb(result):
    global best_score
    best_score = result.best['score']


def counter_cb(result):
    global counter
    counter += 1


# These are taken from the examples in JavaScript code (but made unistrokes)
TGesture = [Vector(30, 7), Vector(103, 7), Vector(66, 7), Vector(66, 87)]
NGesture = [Vector(177, 92), Vector(177, 2), Vector(182, 1), Vector(246, 95),
             Vector(247, 87), Vector(247, 1)]


# dataset that matches N pretty well
Ncandidate = [
    Vector(160, 271), Vector(160, 263), Vector(158, 257), Vector(156, 249),
    Vector(146, 187), Vector(144, 181), Vector(144, 175), Vector(142, 167),
    Vector(140, 113), Vector(140, 107), Vector(140, 103), Vector(140, 99),
    Vector(140, 85), Vector(138, 85), Vector(138, 87), Vector(138, 89),
    Vector(166, 151), Vector(176, 171), Vector(188, 189), Vector(200, 205),
    Vector(238, 263), Vector(242, 269), Vector(244, 273), Vector(246, 277),
    Vector(252, 289), Vector(254, 291), Vector(256, 291), Vector(258, 291),
    Vector(260, 281), Vector(260, 275), Vector(260, 267), Vector(260, 255),
    Vector(254, 189), Vector(254, 175), Vector(254, 161), Vector(254, 147),
    Vector(260, 103), Vector(260, 101), Vector(260, 99), Vector(260, 95),
    Vector(260, 93), Vector(260, 91), Vector(260, 89)
]


class MultistrokeTestCase(unittest.TestCase):

    def setUp(self):
        global best_score
        best_score = 0
        counter = 0

        self.Tinvar = MultistrokeGesture('T', [TGesture],
            orientation_sensitive=False)
        self.Tbound = MultistrokeGesture('T', [TGesture],
            orientation_sensitive=True)
        self.Ninvar = MultistrokeGesture('N', [NGesture],
            orientation_sensitive=False)
        self.Nbound = MultistrokeGesture('N', [NGesture],
            orientation_sensitive=True)

# -----------------------------------------------------------------------------
# Recognizer scheduling
# -----------------------------------------------------------------------------
    def test_immediate(self):
        gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
        r = gdb.recognize([Ncandidate], max_gpf=0)
        self.assertEqual(r._match_ops, 4)
        self.assertEqual(r._completed, 2)
        self.assertEqual(r.progress, 1)
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)

    def test_scheduling(self):
        global best_score
        from kivy.clock import Clock
        gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
        r = gdb.recognize([Ncandidate], max_gpf=1)
        r.bind(on_complete=best_score_cb)

        # _recognize_tick is scheduled here; compares to Tinvar
        Clock.tick()
        self.assertEqual(r.progress, .5)
        self.assertEqual(best_score, .0)

        # Now complete the search operation
        Clock.tick()
        self.assertEqual(r.progress, 1)
        self.assertTrue(best_score > 0.94 and best_score < 0.95)

    def test_scheduling_limits(self):
        global best_score
        from kivy.clock import Clock
        gdb = Recognizer(db=[self.Ninvar])
        tpls = len(self.Ninvar.templates)

        best_score = 0
        gdb.db.append(self.Ninvar)
        r = gdb.recognize([Ncandidate], max_gpf=1)
        r.bind(on_complete=best_score_cb)
        self.assertEqual(r.progress, 0)
        Clock.tick()
        self.assertEqual(r.progress, 0.5)
        self.assertEqual(best_score, 0)
        Clock.tick()
        self.assertEqual(r.progress, 1)
        self.assertTrue(best_score > 0.94 and best_score < 0.95)

        best_score = 0
        gdb.db.append(self.Ninvar)
        r = gdb.recognize([Ncandidate], max_gpf=1)
        r.bind(on_complete=best_score_cb)
        self.assertEqual(r.progress, 0)
        Clock.tick()
        self.assertEqual(r.progress, 1 / 3.)

        Clock.tick()
        self.assertEqual(r.progress, 2 / 3.)
        self.assertEqual(best_score, 0)

        Clock.tick()
        self.assertEqual(r.progress, 1)
        self.assertTrue(best_score > 0.94 and best_score < 0.95)

    def test_parallel_recognize(self):
        global counter
        from kivy.clock import Clock

        counter = 0
        gdb = Recognizer()
        for i in range(9):
            gdb.add_gesture('T', [TGesture], priority=50)
        gdb.add_gesture('N', [NGesture])

        r1 = gdb.recognize([Ncandidate], max_gpf=1)
        r1.bind(on_complete=counter_cb)
        Clock.tick()  # first run scheduled here; 9 left

        r2 = gdb.recognize([Ncandidate], max_gpf=1)
        r2.bind(on_complete=counter_cb)
        Clock.tick()  # 8 left

        r3 = gdb.recognize([Ncandidate], max_gpf=1)
        r3.bind(on_complete=counter_cb)
        Clock.tick()  # 7 left

        # run some immediate searches, should not interfere.
        for i in range(5):
            n = gdb.recognize([TGesture], max_gpf=0)
            self.assertEqual(n.best['name'], 'T')
            self.assertTrue(round(n.best['score'], 1) == 1.0)

        for i in range(6):
            Clock.tick()
        self.assertEqual(counter, 0)
        Clock.tick()
        self.assertEqual(counter, 1)
        Clock.tick()
        self.assertEqual(counter, 2)
        Clock.tick()
        self.assertEqual(counter, 3)

    def test_timeout_case_1(self):
        global best_score
        from kivy.clock import Clock
        from time import sleep

        best_score = 0
        gdb = Recognizer(db=[self.Tbound, self.Ninvar])
        r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.1)
        Clock.tick()  # matches Tbound in this tick
        self.assertEqual(best_score, 0)
        sleep(0.11)
        Clock.tick()  # should match Ninv, but times out (got T)
        self.assertEqual(r.status, 'timeout')
        self.assertEqual(r.progress, .5)
        self.assertTrue(r.best['name'] == 'T')
        self.assertTrue(r.best['score'] < 0.5)

    def test_timeout_case_2(self):
        global best_score
        from kivy.clock import Clock
        from time import sleep

        best_score = 0
        gdb = Recognizer(db=[self.Tbound, self.Ninvar, self.Tinvar])
        r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.2)

        Clock.tick()  # matches Tbound in this tick
        self.assertEqual(best_score, 0)
        sleep(0.1)
        Clock.tick()  # matches Ninvar in this tick
        sleep(0.1)
        Clock.tick()  # should match Tinvar, but times out
        self.assertEqual(r.status, 'timeout')
        self.assertEqual(r.progress, 2 / 3.)
        self.assertTrue(r.best['score'] >= .94 and r.best['score'] <= .95)

    def test_priority_sorting(self):
        gdb = Recognizer()
        gdb.add_gesture('N', [NGesture], priority=10)
        gdb.add_gesture('T', [TGesture], priority=5)

        r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
                        force_priority_sort=True)
        self.assertEqual(r.best['name'], 'T')

        r = gdb.recognize([Ncandidate], goodscore=0.01,
                        force_priority_sort=False, max_gpf=0)
        self.assertEqual(r.best['name'], 'N')

        r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
                        priority=10)
        self.assertEqual(r.best['name'], 'T')

        r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
                        priority=4)
        self.assertEqual(r.best['name'], None)

# -----------------------------------------------------------------------------
# Recognizer - filter tests
# -----------------------------------------------------------------------------
    def test_name_filter(self):
        gdb = Recognizer(db=[self.Ninvar, self.Nbound])
        n = gdb.filter()
        self.assertEqual(len(n), 2)
        n = gdb.filter(name='X')
        self.assertEqual(len(n), 0)

    def test_numpoints_filter(self):
        gdb = Recognizer(db=[self.Ninvar, self.Nbound])
        n = gdb.filter(numpoints=100)
        self.assertEqual(len(n), 0)

        gdb.add_gesture('T', [TGesture], numpoints=100)
        n = gdb.filter(numpoints=100)
        self.assertEqual(len(n), 1)
        n = gdb.filter(numpoints=[100, 16])
        self.assertEqual(len(n), 3)

    def test_numstrokes_filter(self):
        gdb = Recognizer(db=[self.Ninvar, self.Nbound])
        n = gdb.filter(numstrokes=2)
        self.assertEqual(len(n), 0)

        gdb.add_gesture('T', [TGesture, TGesture])
        n = gdb.filter(numstrokes=2)
        self.assertEqual(len(n), 1)
        n = gdb.filter(numstrokes=[1, 2])
        self.assertEqual(len(n), 3)

    def test_priority_filter(self):
        gdb = Recognizer(db=[self.Ninvar, self.Nbound])
        n = gdb.filter(priority=50)
        self.assertEqual(len(n), 0)

        gdb.add_gesture('T', [TGesture], priority=51)
        n = gdb.filter(priority=50)
        self.assertEqual(len(n), 0)
        n = gdb.filter(priority=51)
        self.assertEqual(len(n), 1)

        gdb.add_gesture('T', [TGesture], priority=52)
        n = gdb.filter(priority=[0, 51])
        self.assertEqual(len(n), 1)
        n = gdb.filter(priority=[0, 52])
        self.assertEqual(len(n), 2)
        n = gdb.filter(priority=[51, 52])
        self.assertEqual(len(n), 2)
        n = gdb.filter(priority=[52, 53])
        self.assertEqual(len(n), 1)
        n = gdb.filter(priority=[53, 54])
        self.assertEqual(len(n), 0)

    def test_orientation_filter(self):
        gdb = Recognizer(db=[self.Ninvar, self.Nbound])
        n = gdb.filter(orientation_sensitive=True)
        self.assertEqual(len(n), 1)
        n = gdb.filter(orientation_sensitive=False)
        self.assertEqual(len(n), 1)
        n = gdb.filter(orientation_sensitive=None)
        self.assertEqual(len(n), 2)

        gdb.db.append(self.Tinvar)
        n = gdb.filter(orientation_sensitive=True)
        self.assertEqual(len(n), 1)
        n = gdb.filter(orientation_sensitive=False)
        self.assertEqual(len(n), 2)
        n = gdb.filter(orientation_sensitive=None)
        self.assertEqual(len(n), 3)

# -----------------------------------------------------------------------------
# misc tests
# -----------------------------------------------------------------------------
    def test_resample(self):
        r = kivy.multistroke.resample([Vector(0, 0), Vector(1, 1)], 11)
        self.assertEqual(len(r), 11)
        self.assertEqual(round(r[9].x, 1), 0.9)

        r = kivy.multistroke.resample(TGesture, 25)
        self.assertEqual(len(r), 25)
        self.assertEqual(round(r[12].x), 81)
        self.assertEqual(r[12].y, 7)
        self.assertEqual(TGesture[3].x, r[24].x)
        self.assertEqual(TGesture[3].y, r[24].y)

    def test_rotateby(self):
        r = kivy.multistroke.rotate_by(NGesture, 24)
        self.assertEqual(round(r[2].x, 1), 158.59999999999999)
        self.assertEqual(round(r[2].y, 1), 54.899999999999999)

    def test_transfer(self):
        gdb1 = Recognizer(db=[self.Ninvar])
        gdb2 = Recognizer()
        gdb1.transfer_gesture(gdb2, name='N')

        r = gdb2.recognize([Ncandidate], max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)

    def test_export_import_case_1(self):
        gdb1 = Recognizer(db=[self.Ninvar])
        gdb2 = Recognizer()

        g = gdb1.export_gesture(name='N')
        gdb2.import_gesture(g)

        r = gdb2.recognize([Ncandidate], max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)

    def test_export_import_case_2(self):
        from tempfile import mkstemp
        import os
        gdb1 = Recognizer(db=[self.Ninvar, self.Tinvar])
        gdb2 = Recognizer()
        fh, fn = mkstemp()
        os.close(fh)
        g = gdb1.export_gesture(name='N', filename=fn)

        gdb2.import_gesture(filename=fn)
        os.unlink(fn)

        self.assertEqual(len(gdb1.db), 2)
        self.assertEqual(len(gdb2.db), 1)
        r = gdb2.recognize([Ncandidate], max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)

# ------------------------------------------------------------------------
# Test protractor
# ------------------------------------------------------------------------
    def test_protractor_invariant(self):
        gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
        r = gdb.recognize([NGesture], orientation_sensitive=False,
            max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] == 1.0)

        r = gdb.recognize([NGesture], orientation_sensitive=True,
            max_gpf=0)
        self.assertEqual(r.best['name'], None)
        self.assertEqual(r.best['score'], 0)

        r = gdb.recognize([Ncandidate], orientation_sensitive=False,
            max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)

    def test_protractor_bound(self):
        gdb = Recognizer(db=[self.Tbound, self.Nbound])
        r = gdb.recognize([NGesture], orientation_sensitive=True,
            max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] >= 0.99)

        r = gdb.recognize([NGesture], orientation_sensitive=False,
            max_gpf=0)
        self.assertEqual(r.best['name'], None)
        self.assertEqual(r.best['score'], 0)

        r = gdb.recognize([Ncandidate], orientation_sensitive=True,
            max_gpf=0)
        self.assertEqual(r.best['name'], 'N')
        self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)


if __name__ == '__main__':
    unittest.main()
