def classify(self, track_segment):
past_name = None
N = len(track_segment)
length = 0
for i in range(N - 1):
start = track_segment[i]
stop = track_segment[i + 1]
if start.ele == None or stop.ele == None:
return False
tangens = Track.angle_from_points(None, start, stop,
True) * 100 #проценты
name_steepness = self.check_steepness_slopes(tangens)
if name_steepness != past_name:
if past_name is None:
past_name = name_steepness
continue
if self.check_length_slopes(name_steepness, length):
self.add_steepness_one(name_steepness)
length = 0
past_name = name_steepness
else:
length += Track.distance_from_points(None, start, stop) * 1000
return True
def test_multi_list(self):
benchmark_gpx = GPX()
benchmark_gpx.track = Track()
benchmark_gpx.set_describe("111")
benchmark_gpx.set_name("test1")
benchmark_gpx.set_time("1.01.2000")
benchmark_gpxs = [benchmark_gpx]
benchmark_gpx = GPX()
benchmark_gpx.track = Track()
benchmark_gpx.set_describe("222")
benchmark_gpx.set_name("test2")
benchmark_gpx.set_time("2.02.2000")
benchmark_gpxs.append(benchmark_gpx)
gpxs = None
with open("restoretest2.pickle", 'rb') as f:
gpxs = pickle.load(f)
self.assertTrue(len(gpxs) == len(benchmark_gpxs))
for i in range(len(gpxs)):
self.assertTrue(gpxs[i] == benchmark_gpxs[i])
def classify(self, track_segment):
past_name = None
N = len(track_segment)
length = 0
for i in range(N - 1):
start = track_segment[i]
stop = track_segment[i + 1]
if start.ele == None or stop.ele == None:
return False
angle = Track.angle_from_points(None, start, stop)
name_steepness = self.check_steepness_slopes(angle)
if name_steepness != past_name:
if past_name is None:
past_name = name_steepness
continue
name_length = self.get_length_name(length)
self.add_steepness_one(name_steepness, name_length)
length = 0
past_name = name_steepness
else:
length += Track.distance_from_points(None, start, stop) * 1000
return True
def test_single_list(self):
benchmark_gpx = GPX()
benchmark_gpx.track = Track()
benchmark_gpx.set_describe("111")
benchmark_gpx.set_name("test1")
benchmark_gpx.set_time("1.01.2000")
gpxs = None
benchmark_gpxs = [benchmark_gpx]
with open("restoretest1.pickle", 'rb') as f:
gpxs = pickle.load(f)
self.assertTrue(len(gpxs) == len(benchmark_gpxs))
self.assertTrue(gpxs[0] == benchmark_gpxs[0])
def __gen_gpx(self, data=None):
if data is None:
data = [
self.__get_random_string(),
randint(1, 1000),
"%d.%d.%d" %
(randint(1, 30), randint(1, 12), randint(1970, 2018))
]
gp = GPX()
gp.track = Track()
gp.set_describe(data[0])
gp.set_name(data[1])
gp.set_time(data[2])
return gp
def add_gpx_clicked(self):
data = self.add_gpx_core()
if self.gpx_field_validator(data):
self.stack_redo.clear()
gp = GPX()
gp.track = Track()
gp.set_describe(data[1])
gp.set_name(data[0])
gp.set_time(data[2])
N = self.presenter.get_gpx_row_number()
command = AddCommandGPX(gp, self.gpxs, N)
command.execute()
self.presenter.update_gpx_table()
self.stack_undo.append(command)
def test_add_single_gpx(self, start_val=5):
self.__setup(start_val)
benchmark_data = deepcopy(self.gpxs)
gp = GPX()
gp.track = Track()
gp.set_describe("Test1")
gp.set_name("123")
gp.set_time("1.01.1970")
comm = AddCommandGPX(gp, self.gpxs, self.N)
comm.execute()
benchmark_data.append(deepcopy(gp))
self.assertTrue(len(self.gpxs) == len(benchmark_data))
for i in range(len(benchmark_data)):
self.assertEqual(self.gpxs[i], benchmark_data[i])
def classify_old(self, track_segment):
past_category = 0
N = len(track_segment)
for i in range(N - 2):
start = track_segment[i]
medium = track_segment[i + 1]
stop = track_segment[i + 2]
angle = 180 - Track.turn_angle(None, start, medium, stop)
curr_category = self.check_category(angle)
if curr_category != past_category:
if past_category is None:
past_category = curr_category
continue
self.add_category_one(curr_category)
past_category = curr_category
def classify(self, track_segment):
max_cat = -1
past_category = -1
N = len(track_segment)
for i in range(N - 2):
start = track_segment[i]
medium = track_segment[i + 1]
stop = track_segment[i + 2]
angle = 180 - Track.turn_angle(None, start, medium, stop)
curr_category = self.check_category(angle)
max_cat = max(max_cat, curr_category)
if curr_category == -1 and past_category != -1:
self.add_category_one(max_cat)
max_cat = -1
past_category = curr_category
return True