def main():
params = parameters.Parameters()
params.read(sys.argv[1:])
sim = False
for task in params.task:
if task == "app":
dash_ui.launcher.launch_app(params)
elif task == "help":
if (len(sys.argv) > 2):
params.help(sys.argv[2])
else:
params.help()
elif task == "track":
tracking.track(params)
elif task == "simulate":
simulation.simulate(params)
sim = True
elif task == "postprocess":
postprocessing.postprocess(params, simulated=sim)
elif task == "view":
visualisation.render(params)
elif task == "compare":
trajectories.compare_trajectories(params)
else:
sys.exit(f"ERROR: Task {task} is not yet implemented. Aborting...")
def movie_menu(title, imdb_id):
tracking.track('/Movies/Movie', { 'Title': title })
torrent_infos = []
torrent_provider = SharedCodeService.metaprovider.MetaProvider()
torrent_provider.movies_get_specific_torrents(imdb_id, torrent_infos)
torrent_infos.sort(key=lambda torrent_info: torrent_info.seeders, reverse=True)
object_container = ObjectContainer(title2=title)
for torrent_info in torrent_infos:
seeders_leechers_line = '{0}\nSeeders: {1}, Leechers: {2}'.format(torrent_info.size, torrent_info.seeders, torrent_info.leechers)
movie_object = MovieObject()
SharedCodeService.trakt.movies_fill_movie_object(movie_object, imdb_id)
object_container.title2 = movie_object.title
movie_object.title = torrent_info.release
movie_object.summary = '{0}\n\n{1}'.format(seeders_leechers_line, movie_object.summary)
movie_object.url = torrent_info.url
object_container.add(movie_object)
return object_container
def menu():
tracking.track('/Anime')
object_container = ObjectContainer(title2='Anime')
object_container.add(DirectoryObject(key=Callback(popular_menu, title='Popular', per_page=31), title='Popular', summary='Browse popular anime'))
object_container.add(InputDirectoryObject(key=Callback(search_menu, title='Search', per_page=31), title='Search', summary='Search anime', thumb=R('search.png'), prompt='Search for anime'))
return object_container
def test_track_multiple_t1_swaps_special_example_7(self):
sys.setrecursionlimit(40000)
first_mesh = mesh.load(path.join(dirname(__file__), 'data', 'multiple_t1_example_7_before.mesh'))
second_mesh = mesh.load(path.join(dirname(__file__), 'data', 'multiple_t1_example_7_after.mesh'))
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(first_mesh.elements):
ground_truth[element.id_in_frame] = second_mesh.elements[element_index].id_in_frame
first_mesh.plot(path.join(dirname(__file__),'output','multiple_t1_example_7_before.pdf'))
second_mesh.plot(path.join(dirname(__file__),'output','multiple_t1_example_7_after.pdf'))
tracking.track(first_mesh, second_mesh)
# tracking.find_maximum_common_subgraph(first_mesh, second_mesh)
first_mesh.plot(path.join(dirname(__file__),'output','multiple_t1_example_7_before.pdf'),
color_by_global_id = True, total_number_of_global_ids = first_mesh.get_num_elements())
second_mesh.plot(path.join(dirname(__file__),'output','multiple_t1_example_7_after.pdf'),
color_by_global_id = True, total_number_of_global_ids = first_mesh.get_num_elements())
print 'evaluate tracking'
tracking_success, number_tracked_cells = tracking.evaluate_tracking(first_mesh,
second_mesh,
ground_truth)
def episode_menu(show_title, tvdb_id, season_index, episode_index, first_aired_iso):
tracking.track('/TV Shows/Episode', { 'Title': show_title, 'Season': season_index, 'Episode': episode_index })
torrent_provider = SharedCodeService.metaprovider.MetaProvider()
torrent_infos = []
torrent_provider.tvshows_get_specific_torrents(tvdb_id, season_index, episode_index, first_aired_iso, torrent_infos)
torrent_infos.sort(key=lambda torrent_info: torrent_info.seeders, reverse=True)
object_container = ObjectContainer()
for torrent_info in torrent_infos:
seeders_leechers_line = '{0}\nSeeders: {1}, Leechers: {2}'.format(torrent_info.size, torrent_info.seeders, torrent_info.leechers)
episode_object = EpisodeObject()
SharedCodeService.trakt.tvshows_fill_episode_object(episode_object, tvdb_id, season_index, episode_index)
object_container.title2 = episode_object.title
episode_object.title = torrent_info.release
episode_object.summary = '{0}\n\n{1}'.format(seeders_leechers_line, episode_object.summary)
episode_object.url = torrent_info.url
object_container.add(episode_object)
return object_container
def movie_menu(title, imdb_id):
tracking.track('/Movies/Movie', {'Title': title})
torrent_infos = []
torrent_provider = SharedCodeService.metaprovider.MetaProvider()
torrent_provider.movies_get_specific_torrents(imdb_id, torrent_infos)
torrent_infos.sort(key=lambda torrent_info: torrent_info.seeders,
reverse=True)
object_container = ObjectContainer(title2=title)
for torrent_info in torrent_infos:
seeders_leechers_line = '{0}\nSeeders: {1}, Leechers: {2}'.format(
torrent_info.size, torrent_info.seeders, torrent_info.leechers)
movie_object = MovieObject()
SharedCodeService.trakt.movies_fill_movie_object(movie_object, imdb_id)
object_container.title2 = movie_object.title
movie_object.title = torrent_info.release
movie_object.summary = '{0}\n\n{1}'.format(seeders_leechers_line,
movie_object.summary)
movie_object.url = torrent_info.url
object_container.add(movie_object)
return object_container
def favorites_menu(title):
tracking.track('/TV Shows/' + title)
ids = Dict['tvshows_favorites'] if 'tvshows_favorites' in Dict else []
object_container = ObjectContainer(title2=title)
fill_object_container(object_container, ids)
return object_container
def about_menu():
tracking.track('/About')
object_container = ObjectContainer(title2='About')
object_container.add(DirectoryObject(key=Callback(empty_menu), title='Channel version: {0}'.format(SharedCodeService.common.VERSION), summary='Current version of the BitTorrent channel'))
object_container.add(DirectoryObject(key=Callback(empty_menu), title='Local IP: {0}'.format(Network.Address), summary='Plex Media Server Local IP'))
object_container.add(DirectoryObject(key=Callback(empty_menu), title='Public IP: {0}'.format(Network.PublicAddress), summary='Plex Media Server Public IP'))
return object_container
def run_tracking_task(nclicks, active_file, params_json):
params = Parameters(json.loads(params_json))
params._params = json.loads(params_json)
if ".tif" in active_file:
params.name = active_file.replace('.tif','')
tracking.track(params)
return ["", 1, True, 'render-current-trajectories']
def onChange(self, trackbarValue):
#set video to starting frame
self.video.set(cv2.CAP_PROP_POS_FRAMES, self.start)
cnts, image_edged3, image_contours = imagePros(self.fileName,
option='vid')
cells = []
bboxes = []
global x
global y
global w
global h
global counter
counter = 0
cellTags = []
#Ignore contours that do not satisfy size criteria
for i in cnts:
if cv2.contourArea(i) < 700 or cv2.contourArea(i) > 6000:
continue
hull = cv2.convexHull(i)
cv2.drawContours(image_contours, [hull], 0, (34, 255, 34), 2)
x, y, w, h = cv2.boundingRect(i)
#save coordinates in bboxes array
bboxes.append([x, y, w, h])
M = cv2.moments(i)
cx = int(M['m10'] / M['m00'])
cy = int(M['m01'] / M['m00'])
#save centers in cells array
cells.append([cx, cy])
cellLet = chr(counter + 67)
cellTags.append(counter + 67)
cv2.putText(image_contours, cellLet, (cx, cy),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (225, 0, 255), 2)
counter = counter + 1
cv2.putText(image_contours, "cell count: " + str(counter), (10, 40),
cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)
#show starting video frame with each cell tagged
cv2.imshow("cellVid", image_contours)
k = cv2.waitKey()
print(cellTags)
print(k)
if k == 27:
pass
elif k in cellTags:
#selected cell's coordinates are sent to tracking
print("key")
cellnumber = k - 67
print(len(bboxes))
print(cellnumber)
tracking.track(bboxes[cellnumber][0], bboxes[cellnumber][1],
bboxes[cellnumber][2], bboxes[cellnumber][3],
cv2.CAP_PROP_POS_FRAMES, self.fileName)
pass
def menu():
tracking.track('/Movies')
object_container = ObjectContainer(title2='Movies')
object_container.add(DirectoryObject(key=Callback(movies_menu, title='Popular', page='/movies/trending', per_page=31), title='Popular', summary='Browse popular movies'))
object_container.add(DirectoryObject(key=Callback(movies_menu, title='Rating', page='/movies/popular', per_page=31), title='Rating', summary='Browse highly-rated movies'))
object_container.add(DirectoryObject(key=Callback(genres_menu, title='Genres'), title='Genres', summary='Browse movies by genre'))
object_container.add(InputDirectoryObject(key=Callback(search_menu, title='Search', per_page=31), title='Search', summary='Search movies', thumb=R('search.png'), prompt='Search for movies'))
return object_container
def genres_menu(title):
tracking.track('/Movies/' + title)
genres = SharedCodeService.trakt.movies_genres()
object_container = ObjectContainer(title2=title)
for genre in genres:
object_container.add(DirectoryObject(key=Callback(genre_menu, title=genre[0], genre=genre[1], per_page=31), title=genre[0]))
return object_container
def search_menu(title, query, per_page, count=0):
tracking.track('/Movies/Search', { 'Query': query })
ids = []
count = SharedCodeService.trakt.movies_search(query, ids)
object_container = ObjectContainer(title2=title)
fill_object_container(object_container, ids)
return object_container
def menu():
tracking.track('/TV Shows')
object_container = ObjectContainer(title2='TV Shows')
object_container.add(DirectoryObject(key=Callback(shows_menu, title='Popular', page='/shows/trending', per_page=31), title='Popular', summary='Browse popular TV shows'))
object_container.add(DirectoryObject(key=Callback(shows_menu, title='Rating', page='/shows/popular', per_page=31), title='Rating', summary='Browse highly-rated TV shows'))
object_container.add(DirectoryObject(key=Callback(genres_menu, title='Genres'), title='Genres', summary='Browse TV shows by genre'))
object_container.add(DirectoryObject(key=Callback(favorites_menu, title='Favorites'), title='Favorites', summary='Browse your favorite TV shows', thumb=R('favorites.png')))
object_container.add(InputDirectoryObject(key=Callback(search_menu, title='Search', per_page=31), title='Search', summary='Search TV shows', thumb=R('search.png'), prompt='Search for TV shows'))
return object_container
def remove_from_favorites(title, show_title, tvdb_id):
tracking.track('/TV Shows/FavRemove', { 'Title': show_title })
if 'tvshows_favorites' in Dict and tvdb_id in Dict['tvshows_favorites']:
Dict['tvshows_favorites'].remove(tvdb_id)
Dict.Save()
object_container = ObjectContainer(title2=title)
object_container.header = 'Remove from Favorites'
object_container.message = '{0} removed from Favorites'.format(show_title)
return object_container
def genre_menu(title, genre, per_page, count=0):
tracking.track('/Movies/Genre', { 'Genre': title })
ids = []
count = SharedCodeService.trakt.get_ids_from_page('/movies/popular/' + genre, ids, count, per_page)
object_container = ObjectContainer(title2=title)
fill_object_container(object_container, ids)
object_container.add(NextPageObject(key=Callback(genre_menu, title=title, genre=genre, per_page=per_page, count=count), title="More..."))
return object_container
def movies_menu(title, page, per_page, count=0):
tracking.track('/Movies/' + title)
ids = []
count = SharedCodeService.trakt.get_ids_from_page(page, ids, count, per_page)
object_container = ObjectContainer(title2=title)
fill_object_container(object_container, ids)
object_container.add(NextPageObject(key=Callback(movies_menu, title=title, page=page, per_page=per_page, count=count), title="More..."))
return object_container
def main():
cap = cv2.VideoCapture(1)
# mask
while (True):
ret, frame = cap.read()
if frame is None:
#print("frame is None")
continue
img = processImage(frame)
cv2.imshow('Image', img)
key = cv2.waitKey(1) & 0xFF
if doneBuilding():
if key == ord('m'):
toggleMask(img)
if key == ord('p'):
break
print("made mask")
print("searching for bot...")
# plan
botLoc = None
while (botLoc is None):
ret, frame = cap.read()
botLoc = tracking.track(frame)
print("found bot at", botLoc)
print("initializing bot...")
bot = robot(botLoc)
print("initialized bot!")
print("finding path...")
ret, frame = cap.read()
img = processImage(frame)
path = findPath(img, botLoc)
print("found it")
bot.followLine(path)
# move
while (True):
ret, frame = cap.read()
img = processImage(frame)
botLoc = tracking.track(frame)
# print("bot location:", botLoc)
if botLoc == (None, None):
continue
bot.update(botLoc)
def season_menu(title, show_title, tvdb_id, season_index):
tracking.track('/TV Shows/Season', { 'Title': show_title, 'Season': season_index })
object_container = ObjectContainer(title2=title)
for episode_index in SharedCodeService.trakt.tvshows_get_season_episode_index_list(tvdb_id, season_index):
directory_object = DirectoryObject()
episode_data = SharedCodeService.trakt.tvshows_fill_episode_object(directory_object, tvdb_id, season_index, episode_index)
directory_object.title = str(episode_index) + '. ' + directory_object.title
directory_object.key = Callback(episode_menu, show_title=show_title, tvdb_id=tvdb_id, season_index=season_index, episode_index=episode_index, first_aired_iso=episode_data['first_aired_iso'])
object_container.add(directory_object)
return object_container
def add_to_favorites(title, show_title, tvdb_id):
tracking.track('/TV Shows/FavAdd', { 'Title': show_title })
if 'tvshows_favorites' not in Dict:
Dict['tvshows_favorites'] = []
if tvdb_id not in Dict['tvshows_favorites']:
Dict['tvshows_favorites'].append(tvdb_id)
Dict.Save()
object_container = ObjectContainer(title2=title)
object_container.header = 'Add to Favorites'
object_container.message = '{0} added to Favorites'.format(show_title)
return object_container
def test_plot_collection_into_separate_figure(self):
"""plot a polygon collection into a figure designed by us
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(5, 5)
print 'start to copy'
mesh_two = copy.deepcopy(mesh_one)
print 'stop to copy'
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
tracked_ids = tracking.track(mesh_one, mesh_two)
# figure properties
figuresize = (4, 2.75)
font = {'size': 10}
plt.rc('font', **font)
mesh_figure = plt.figure(figsize=figuresize)
ax = plt.axes([0, 0, 1, 1])
polygon_collection = mesh_two.get_polygon_collection(
color_by_global_id=True,
total_number_of_global_ids=mesh_one.get_num_elements())
mesh_figure.gca().add_collection(polygon_collection)
mesh_figure.gca().set_aspect('equal')
mesh_figure.gca().autoscale_view()
plt.axis('off')
filename = path.join(dirname(__file__), 'output',
'own_visualisation_figure.pdf')
mesh_figure.savefig(filename, bbox_inches='tight')
def make_permutation_plot(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'permutation'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all, plotname, figuresize)
def make_general_division_plot(figuresize):
"""We load a mesh where two maximum common subgraphs will be identified, and track the division event"""
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.divide_element_with_frame_id_in_direction(most_central_element.id_in_frame, [1.0, 1.0])
tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'division_general'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all, plotname, figuresize)
def make_death_plots(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_two = copy.deepcopy(mesh_one)
# First pick a cell in the centre
mesh_centre = mesh_two.calculate_centre()
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'cell_death'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all,
plotname, figuresize)
def make_death_plots(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_two = copy.deepcopy(mesh_one)
# First pick a cell in the centre
mesh_centre = mesh_two.calculate_centre()
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track( mesh_one, mesh_two )
plotname = 'cell_death'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all, plotname, figuresize)
def make_permutation_plot(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[
element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'permutation'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all,
plotname, figuresize)
def make_general_division_plot(figuresize):
"""We load a mesh where two maximum common subgraphs will be identified, and track the division event"""
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[
element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.divide_element_with_frame_id_in_direction(
most_central_element.id_in_frame, [1.0, 1.0])
tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'division_general'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all,
plotname, figuresize)
def runme(input_vid_path, background_image_path, s_initial):
# 1 - stabilize the input vid
stabilized_vid = st.stabilize(input_vid_path)
# 2 - subtract background from stabilized video
print("Starting trimap")
trimap_folder, trimap_vid = tri.trimap(stabilized_vid)
print("Done with trimap")
# 3 - apply matting
print("Starting matting")
matted_vid = mt.add_background_image(trimap_folder, stabilized_vid,
background_image_path)
print("Done with matting")
# generate frames folder
ut.save_video_frames(matted_vid, folder_name="matted_vid_4_frames")
# 4 - apply tracking
print("Starting tracking")
output_vid = tr.track("matted_vid_4_frames", s_initial)
# 5 - generate the output video from the tracked frames
ut.create_video_from_image_folder("tracked_images",
"OUTPUT.avi",
shape=(555, 416))
print("Done tracking")
return output_vid
def test_plot_collection_into_separate_figure(self):
"""plot a polygon collection into a figure designed by us
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(5,5)
print 'start to copy'
mesh_two = copy.deepcopy(mesh_one)
print 'stop to copy'
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
tracked_ids = tracking.track(mesh_one, mesh_two)
# figure properties
figuresize = (4,2.75)
font = {'size' : 10}
plt.rc('font', **font)
mesh_figure = plt.figure(figsize = figuresize)
ax = plt.axes([0,0,1,1])
polygon_collection = mesh_two.get_polygon_collection(color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements())
mesh_figure.gca().add_collection(polygon_collection)
mesh_figure.gca().set_aspect('equal')
mesh_figure.gca().autoscale_view()
plt.axis('off')
filename = path.join(dirname(__file__),'output','own_visualisation_figure.pdf')
mesh_figure.savefig(filename, bbox_inches = 'tight')
def main(model=Model.DECISION_TREE, seed=None):
original_train, original_validate = load_data()
train, validate = encode(original_train, original_validate)
with tracking.track() as track:
track.set_model(model)
model, params = train_model(train, model, seed)
track.log_params(params)
validation_predictions = make_predictions(model, validate)
print("Calculating metrics")
evaluation_metrics = {
'nwrmsle':
evaluation.nwrmsle(validation_predictions,
validate['unit_sales'].values,
validate['perishable'].values),
'r2_score':
metrics.r2_score(y_true=validate['unit_sales'].values,
y_pred=validation_predictions)
}
track.log_metrics(evaluation_metrics)
write_predictions_and_score(evaluation_metrics, model,
original_train.columns)
print("Evaluation done with metrics {}.".format(
json.dumps(evaluation_metrics)))
def xest_track_shuffled_2_by_2_mesh(self):
""" This tests whether we can identify cells after they got shuffled (2 by 2)
This test is known to fail: due to the symmetry of the problem cells tend to
be mapped in the wrong order.
"""
mesh_one = mesh.creation.generate_hexagonal(2,2)
mesh_two = mesh.creation.generate_hexagonal(2,2)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_in_reverse_order()
id_map = tracking.track(mesh_one, mesh_two)
network_one = mesh_one.generate_network()
network_two = mesh_two.generate_network()
subgraph_network = tracking.generate_subgraph_network(mesh_two, id_map)
self.assertEqual(len(id_map), 4)
for index_one in id_map:
element_one = mesh_one.get_element_with_frame_id(index_one)
element_two = mesh_two.get_element_with_global_id(id_map[index_one])
self.assertEqual(element_one.get_num_nodes(), element_two.get_num_nodes())
self.assertEqual(network_one.degree(index_one), network_two.degree(id_map[index_one]))
self.assertAlmostEqual(element_one.calculate_area(), element_two.calculate_area())
np.testing.assert_almost_equal(element_one.calculate_centroid(), element_two.calculate_centroid())
def xest_track_shuffled_3_by_3_mesh(self):
""" This tests whether we can identify cells after they got shuffled (3 by 3)
"""
mesh_one = mesh.creation.generate_hexagonal(3,3)
mesh_two = mesh.creation.generate_hexagonal(3,3)
mesh_one.assign_frame_ids_in_order()
mesh_one.plot(path.join(dirname(__file__),'output','mesh_one.pdf'))
mesh_two.assign_frame_ids_randomly()
mesh_two.plot(path.join(dirname(__file__),'output','mesh_two_before_tracking.pdf'))
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_two.plot(path.join(dirname(__file__),'output','mesh_two_after_tracking.pdf'), color_by_global_id = True, total_number_of_global_ids = 9)
network_one = mesh_one.generate_network()
network_two = mesh_two.generate_network()
subgraph_network = tracking.generate_subgraph_network(mesh_two, tracked_ids)
self.assertEqual(len(tracked_ids), 9)
for global_id in tracked_ids:
element_one = mesh_one.get_element_with_frame_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEqual(element_one.get_num_nodes(), element_two.get_num_nodes())
self.assertEqual(network_one.degree(element_one.id_in_frame), network_two.degree(element_two.id_in_frame))
self.assertAlmostEqual(element_one.calculate_area(), element_two.calculate_area())
np.testing.assert_almost_equal(element_one.calculate_centroid(), element_two.calculate_centroid())
def test_track_function_on_second_data(self):
"""Test tracking function on second data pair"""
mesh_sequence = mesh.read_sequence_from_data(
path.join(dirname(__file__), 'data', 'first_few_frames'))
first_mesh = mesh_sequence[1]
second_mesh = mesh_sequence[2]
start_time = time.clock()
tracked_ids = tracking.track(first_mesh, second_mesh)
end_time = time.clock()
print 'total time for second data pair is:'
print end_time - start_time
first_mesh.plot(
path.join(dirname(__file__), 'output',
'second_mesh_tracked_with_third_total.pdf'),
color_by_global_id=True,
total_number_of_global_ids=first_mesh.get_num_elements())
second_mesh.plot(
path.join(dirname(__file__), 'output',
'third_mesh_tracked_total.pdf'),
color_by_global_id=True,
total_number_of_global_ids=first_mesh.get_num_elements())
def test_track_very_large_random_mesh(self):
"""generate a small random mesh and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(30,30)
print 'start to copy'
mesh_two = copy.deepcopy(mesh_one)
print 'stop to copy'
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
mesh_one.plot(path.join(dirname(__file__),'output','very_large_random_mesh_one.pdf'))
mesh_two.plot(path.join(dirname(__file__),'output','very_large_random_mesh_two_before_tracking.pdf'))
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_two.plot(path.join(dirname(__file__),'output','very_large_random_mesh_after_tracking.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements())
network_one = mesh_one.generate_network()
network_two = mesh_two.generate_network()
self.assertEqual( len(tracked_ids), mesh_one.get_num_elements())
for global_id in tracked_ids:
element_one = mesh_one.get_element_with_frame_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEqual(element_one.get_num_nodes(), element_two.get_num_nodes())
self.assertEqual(network_one.degree(element_one.id_in_frame), network_two.degree(element_two.id_in_frame))
self.assertAlmostEqual(element_one.calculate_area(), element_two.calculate_area())
np.testing.assert_almost_equal(element_one.calculate_centroid(), element_two.calculate_centroid())
def test_track_function_on_first_data(self):
"""See whether we can fully track the mesh using the track function of the tracking module"""
mesh_sequence = mesh.read_sequence_from_data(
path.join(dirname(__file__), 'data', 'first_few_frames'))
first_mesh = mesh_sequence[0]
second_mesh = mesh_sequence[1]
start_time = time.clock()
tracked_ids = tracking.track(first_mesh, second_mesh)
end_time = time.clock()
print 'total time for first data pair is:'
print end_time - start_time
first_mesh.plot(
path.join(dirname(__file__), 'output',
'first_mesh_tracked_total.pdf'),
color_by_global_id=True,
total_number_of_global_ids=first_mesh.get_num_elements())
second_mesh.plot(
path.join(dirname(__file__), 'output',
'second_mesh_tracked_total.pdf'),
color_by_global_id=True,
total_number_of_global_ids=first_mesh.get_num_elements())
def xest_track_cell_death(self):
"""track a cell death event and identify the cells that are involved in rearrangement"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_one.save(
path.join(dirname(__file__), 'output', 'death_mesh_one.mesh'))
mesh_two = copy.deepcopy(mesh_one)
# mesh_one = mesh.load('death_mesh_one.mesh')
# mesh_two = mesh.load('death_mesh_two.mesh')
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[
element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
mesh_one.plot(
path.join(dirname(__file__), 'output',
'not_tracked_mesh_before_death.pdf'))
mesh_two.plot(
path.join(dirname(__file__), 'output',
'not_tracked_mesh_after_death.pdf'))
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_one.plot(path.join(dirname(__file__), 'output',
'tracked_mesh_before_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
mesh_two.plot(path.join(dirname(__file__), 'output',
'tracked_mesh_after_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
# make sure that the entire mesh was tracked (except for the dead cell)
dangling_elements_one = mesh_one.get_dangling_element_ids(
ground_truth.keys())
self.assertGreaterEqual(
len(tracked_ids),
max(mesh_one.get_num_elements() - 4,
mesh_one.get_num_elements() - len(dangling_elements_one) - 1))
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals(ground_truth[element_one.id_in_frame],
element_two.id_in_frame)
plt.close('all')
def Main():
Log.Info('============================================')
Log.Info('Client:')
Log.Info(' - Product: {0}'.format(Client.Product))
Log.Info(' - Platform: {0}'.format(Client.Platform))
Log.Info('============================================')
tracking.track('/')
object_container = ObjectContainer(title2=TITLE)
object_container.add(DirectoryObject(key=Callback(anime_menu.menu), title='Anime', summary='Browse anime'))
object_container.add(DirectoryObject(key=Callback(movies_menu.menu), title='Movies', summary='Browse movies'))
object_container.add(DirectoryObject(key=Callback(tvshows_menu.menu), title='TV Shows', summary="Browse TV shows"))
object_container.add(PrefsObject(title='Preferences', summary='Preferences for BitTorrent channel'))
object_container.add(DirectoryObject(key=Callback(about_menu), title='About', summary='About BitTorrent channel', thumb=R('about.png')))
return object_container
def tvshow_menu(title, tvdb_id):
tracking.track('/TV Shows/TV Show', { 'Title': title })
object_container = ObjectContainer(title2=title)
if 'tvshows_favorites' in Dict and tvdb_id in Dict['tvshows_favorites']:
object_container.add(DirectoryObject(key=Callback(remove_from_favorites, title='Remove from Favorites', show_title=title, tvdb_id=tvdb_id), title='Remove from Favorites', summary='Remove TV show from Favorites', thumb=R('favorites.png')))
else:
object_container.add(DirectoryObject(key=Callback(add_to_favorites, title='Add to Favorites', show_title=title, tvdb_id=tvdb_id), title='Add to Favorites', summary='Add TV show to Favorites', thumb=R('favorites.png')))
for season_index in SharedCodeService.trakt.tvshows_get_season_index_list(tvdb_id):
season_object = SeasonObject()
SharedCodeService.trakt.tvshows_fill_season_object(season_object, tvdb_id, season_index)
season_object.key = Callback(season_menu, title=season_object.title, show_title=title, tvdb_id=tvdb_id, season_index=season_object.index)
season_object.rating_key = '{0}-{1}-{2}'.format(title, tvdb_id, season_index)
object_container.add(season_object)
return object_container
def test_translation_special_case(self):
"""load first random mesh, move it, and track it.
"""
sys.setrecursionlimit(40000)
large_mesh = mesh.load(path.join(dirname(__file__),'data','special_translation_mesh_one.mesh'))
large_mesh.assign_frame_ids_in_order()
mesh_one = large_mesh.copy_region_of_interest((3,10),(-1,9))
mesh_two = large_mesh.copy_region_of_interest((5,12),(-1,9))
# Build ground truth
ground_truth_indices = {}
for element_index, element in enumerate(mesh_one.elements):
if element.id_in_frame in mesh_two.frame_id_dictionary:
ground_truth_indices[element_index] = mesh_two.frame_id_dictionary[element.id_in_frame]
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
if element_index in ground_truth_indices:
ground_truth[element.id_in_frame] = mesh_two.elements[ground_truth_indices[element_index]].id_in_frame
print 'call tracker'
tracked_ids = tracking.track(mesh_one, mesh_two)
# tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
print 'tracker returned'
mesh_one.plot(path.join(dirname(__file__),'output', 'special_translation_mesh_one.pdf'), color_by_global_id = True,
total_number_of_global_ids = len(tracked_ids) )
mesh_two.plot(path.join(dirname(__file__),'output', 'special_translation_mesh_two.pdf'), color_by_global_id = True,
total_number_of_global_ids = len(tracked_ids) )
network_one = mesh_one.generate_network()
network_two = mesh_two.generate_network()
self.assertEqual( len(tracked_ids), len(ground_truth) )
# for frame_id in ground_truth:
# if mesh_one.get_element_with_frame_id(frame_id).global_id == None:
# print 'element with this frame id did not get tracked:'
# print frame_id
for global_id in tracked_ids:
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEqual(element_one.get_num_nodes(), element_two.get_num_nodes())
self.assertAlmostEqual(element_one.calculate_area(), element_two.calculate_area())
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals( ground_truth[element_one.id_in_frame], element_two.id_in_frame )
def make_t1_plots(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[
element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# Perform T1 swap on mesh two
# First pick a node in the centre
mesh_centre = mesh_two.calculate_centre()
# pick the node closest to the centre
min_distance = 3 * mesh_two.calculate_height()
for node in mesh_two.nodes:
distance = np.linalg.norm(node.position - mesh_centre)
if distance < min_distance:
min_distance = distance
most_central_node = node
# pick a node that shares an edge with this central node
for local_index, element_node in enumerate(
most_central_node.adjacent_elements[0].nodes):
if element_node.id == most_central_node.id:
num_nodes_this_element = most_central_node.adjacent_elements[
0].get_num_nodes()
one_edge_node = most_central_node.adjacent_elements[0].nodes[
(local_index + 1) % num_nodes_this_element]
break
mesh_two.perform_t1_swap(most_central_node.id, one_edge_node.id)
tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 't1_swap'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all,
plotname, figuresize)
def episode_menu(show_title, tvshow_id, season_index, episode_index,
first_aired_iso):
tracking.track('/TV Shows/Episode', {
'Title': show_title,
'Season': season_index,
'Episode': episode_index
})
torrent_provider = SharedCodeService.metaprovider.MetaProvider()
torrent_infos = []
torrent_provider.tvshows_get_specific_torrents(tvshow_id, season_index,
episode_index,
first_aired_iso,
torrent_infos)
torrent_infos.sort(key=lambda torrent_info: torrent_info.seeders,
reverse=True)
object_container = ObjectContainer()
for torrent_info in torrent_infos:
seeders_leechers_line = '{0}\nSeeders: {1}, Leechers: {2}'.format(
torrent_info.size, torrent_info.seeders, torrent_info.leechers)
episode_object = EpisodeObject()
SharedCodeService.trakt.tvshows_fill_episode_object(
episode_object, tvshow_id, season_index, episode_index)
object_container.title2 = episode_object.title
episode_object.title = torrent_info.release
episode_object.summary = '{0}\n\n{1}'.format(seeders_leechers_line,
episode_object.summary)
episode_object.url = torrent_info.url
object_container.add(episode_object)
return object_container
def search_menu(title, query, per_page, movie_count=0):
tracking.track('/Anime/Search', { 'Query': query })
torrent_infos = []
torrent_provider = SharedCodeService.metaprovider.MetaProvider()
torrent_provider.anime_search(query, torrent_infos)
torrent_infos.sort(key=lambda torrent_info: torrent_info.seeders, reverse=True)
object_container = ObjectContainer(title2=title)
for torrent_info in torrent_infos:
seeders_leechers_line = '{0}\nSeeders: {1}, Leechers: {2}'.format(torrent_info.size, torrent_info.seeders, torrent_info.leechers)
videoclip_object = VideoClipObject()
videoclip_object.title = torrent_info.title
videoclip_object.summary = seeders_leechers_line
videoclip_object.url = torrent_info.url
object_container.add(videoclip_object)
return object_container
def test_track_division_standard_case(self):
"""We load a mesh where only one maximum common subgraph should be identified, and track the division event"""
mesh_one = mesh.load(
path.join(dirname(__file__), 'data',
'standard_simple_division_one.mesh'))
mesh_two = mesh.load(
path.join(dirname(__file__), 'data',
'standard_simple_division_two.mesh'))
# First pick a cell in the centre
mesh_centre = mesh_two.calculate_centre()
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[
element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.divide_element_with_frame_id(most_central_element.id_in_frame)
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_one.plot(path.join(dirname(__file__), 'output',
'tracked_standard_mesh_before_division.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
mesh_two.plot(path.join(dirname(__file__), 'output',
'tracked_standard_mesh_after_division.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
# make sure that the entire mesh was tracked (except for the dead cell)
self.assertEqual(len(tracked_ids), mesh_one.get_num_elements() - 2)
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals(ground_truth[element_one.id_in_frame],
element_two.id_in_frame)
plt.close('all')
def test_visualise_search(self):
"""generate a small random mesh and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(5,5)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_two.plot(path.join(dirname(__file__),'output','visualisation_mesh_after_tracking.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements())
def make_t1_plots(figuresize):
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# Perform T1 swap on mesh two
# First pick a node in the centre
mesh_centre = mesh_two.calculate_centre()
# pick the node closest to the centre
min_distance = 3*mesh_two.calculate_height()
for node in mesh_two.nodes:
distance = np.linalg.norm(node.position - mesh_centre)
if distance < min_distance:
min_distance = distance
most_central_node = node
# pick a node that shares an edge with this central node
for local_index, element_node in enumerate(most_central_node.adjacent_elements[0].nodes):
if element_node.id == most_central_node.id:
num_nodes_this_element = most_central_node.adjacent_elements[0].get_num_nodes()
one_edge_node = most_central_node.adjacent_elements[0].nodes[(local_index+1)%num_nodes_this_element]
break
mesh_two.perform_t1_swap( most_central_node.id, one_edge_node.id )
tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
tracked_ids_all = tracking.track( mesh_one, mesh_two )
plotname = 't1_swap'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all, plotname, figuresize)
def xest_track_cell_death(self):
"""track a cell death event and identify the cells that are involved in rearrangement"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_one.save(path.join(dirname(__file__),'output','death_mesh_one.mesh'))
mesh_two = copy.deepcopy(mesh_one)
# mesh_one = mesh.load('death_mesh_one.mesh')
# mesh_two = mesh.load('death_mesh_two.mesh')
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
mesh_one.plot(path.join(dirname(__file__),'output','not_tracked_mesh_before_death.pdf' ))
mesh_two.plot(path.join(dirname(__file__),'output','not_tracked_mesh_after_death.pdf' ))
tracked_ids = tracking.track( mesh_one, mesh_two )
mesh_one.plot(path.join(dirname(__file__),'output','tracked_mesh_before_death.pdf'), color_by_global_id = True,
total_number_of_global_ids = len( tracked_ids ) )
mesh_two.plot(path.join(dirname(__file__),'output','tracked_mesh_after_death.pdf'), color_by_global_id = True,
total_number_of_global_ids = len( tracked_ids ) )
# make sure that the entire mesh was tracked (except for the dead cell)
dangling_elements_one = mesh_one.get_dangling_element_ids(ground_truth.keys())
self.assertGreaterEqual(len(tracked_ids),
max(mesh_one.get_num_elements() - 4,
mesh_one.get_num_elements() - len(dangling_elements_one) - 1))
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals( ground_truth[element_one.id_in_frame], element_two.id_in_frame )
plt.close('all')
def test_visualise_search(self):
"""generate a small random mesh and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(5, 5)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
tracked_ids = tracking.track(mesh_one, mesh_two)
mesh_two.plot(path.join(dirname(__file__), 'output',
'visualisation_mesh_after_tracking.pdf'),
color_by_global_id=True,
total_number_of_global_ids=mesh_one.get_num_elements())
def xest_track_9_by_9_random_mesh(self):
"""generate a small random mesh and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_one.save(path.join(dirname(__file__),'output','nine_by_nine_permutation_mesh_one.mesh'))
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
mesh_one.plot(path.join(dirname(__file__),'output','larger_random_mesh_one.pdf'))
mesh_two.plot(path.join(dirname(__file__),'output','larger_random_mesh_two_before_tracking.pdf'))
tracked_ids = tracking.track(mesh_one, mesh_two)
dangling_elements_one = mesh_one.get_dangling_element_ids(ground_truth.keys())
self.assertGreaterEqual(len(tracked_ids),
max(mesh_one.get_num_elements() - 3,
mesh_one.get_num_elements() - len(dangling_elements_one)))
mesh_one.plot(path.join(dirname(__file__),'output','nine_by_nine_permuation_mesh_before.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements())
mesh_two.plot(path.join(dirname(__file__),'output','nine_by_nine_permuation_mesh_after.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements())
network_one = mesh_one.generate_network()
network_two = mesh_two.generate_network()
for global_id in tracked_ids:
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEqual(element_one.get_num_nodes(), element_two.get_num_nodes())
self.assertEqual(network_one.degree(element_one.id_in_frame), network_two.degree(element_two.id_in_frame))
self.assertAlmostEqual(element_one.calculate_area(), element_two.calculate_area())
np.testing.assert_almost_equal(element_one.calculate_centroid(), element_two.calculate_centroid())
plt.close('all')
def make_translation_plots(figuresize):
sys.setrecursionlimit(40000)
large_mesh = mesh.creation.generate_random_tesselation(15, 8)
large_mesh.assign_frame_ids_in_order()
mesh_one = large_mesh.copy_region_of_interest((3, 10), (-1, 9))
mesh_two = large_mesh.copy_region_of_interest((5, 12), (-1, 9))
ground_truth_indices = {}
for element_index, element in enumerate(mesh_one.elements):
if element.id_in_frame in mesh_two.frame_id_dictionary:
ground_truth_indices[element_index] = mesh_two.frame_id_dictionary[
element.id_in_frame]
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
if element_index in ground_truth_indices:
ground_truth[element.id_in_frame] = mesh_two.elements[
ground_truth_indices[element_index]]
tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
mesh_one.index_global_ids()
mesh_two.index_global_ids()
tracked_ids_all = []
tracked_ids_all = tracking.track(mesh_one, mesh_two)
plotname = 'translation'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all,
plotname, figuresize)
def make_translation_plots(figuresize):
sys.setrecursionlimit(40000)
large_mesh = mesh.creation.generate_random_tesselation(15,8)
large_mesh.assign_frame_ids_in_order()
mesh_one = large_mesh.copy_region_of_interest((3,10),(-1,9))
mesh_two = large_mesh.copy_region_of_interest((5,12),(-1,9))
ground_truth_indices = {}
for element_index, element in enumerate(mesh_one.elements):
if element.id_in_frame in mesh_two.frame_id_dictionary:
ground_truth_indices[element_index] = mesh_two.frame_id_dictionary[element.id_in_frame]
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
if element_index in ground_truth_indices:
ground_truth[element.id_in_frame] = mesh_two.elements[ground_truth_indices[element_index]]
tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
for element in mesh_one.elements:
element.global_id = None
for element in mesh_two.elements:
element.global_id = None
mesh_one.index_global_ids()
mesh_two.index_global_ids()
tracked_ids_all = []
tracked_ids_all = tracking.track( mesh_one, mesh_two )
plotname = 'translation'
make_difference_plot(mesh_one, mesh_two, tracked_ids, tracked_ids_all, plotname, figuresize)
def test_track_special_case(self):
"""track a cell death event and identify the cells that are involved in rearrangement"""
sys.setrecursionlimit(40000)
mesh_one = mesh.load(
path.join(dirname(__file__), 'data',
'special_death_mesh_one.mesh'))
mesh_two = mesh.load(
path.join(dirname(__file__), 'data',
'special_death_mesh_two.mesh'))
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[
element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
mesh_one.plot(
path.join(dirname(__file__), 'output',
'not_tracked_mesh_before_death.pdf'))
mesh_two.plot(
path.join(dirname(__file__), 'output',
'not_tracked_mesh_after_death.pdf'))
tracked_ids = tracking.track(mesh_one, mesh_two)
#
# mesh_one.plot('special_tracked_mesh_before_death.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
# mesh_two.plot('special_tracked_mesh_after_death.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
# tracked_ids = tracking.find_maximum_common_subgraph( mesh_one, mesh_two )
# subgraph_finder = tracking.LocalisedSubgraphFinder(mesh_one, mesh_two)
# subgraph_finder.find_maximum_common_subgraph()
# tracked_ids = tracking.find_maximum_common_subgraph(mesh_one, mesh_two)
mesh_one.plot(path.join(dirname(__file__), 'output',
'special_tracked_mesh_before_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
mesh_two.plot(path.join(dirname(__file__), 'output',
'special_tracked_mesh_after_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
# largest_mappings = subgraph_finder.largest_mappings
#
# for mapping_index, large_mapping in enumerate(largest_mappings):
#
# tracked_ids = []
#
# for element_one in mesh_one.elements:
# element_one.global_id = None
#
# for element_two in mesh_two.elements:
# element_two.global_id = None
#
# for global_id, frame_one_id in enumerate(large_mapping):
# mesh_one.get_element_with_frame_id(frame_one_id).global_id = global_id
# mesh_two.get_element_with_frame_id(large_mapping[frame_one_id]).global_id = global_id
# tracked_ids.append(global_id)
#
# mesh_one.index_global_ids()
# mesh_two.index_global_ids()
#
# mesh_one.plot('mesh_special_before_death_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
# mesh_two.plot('mesh_special_after_death_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
#
# make sure that the entire mesh was tracked (except for the dead cell)
self.assertEqual(len(tracked_ids), mesh_two.get_num_elements() - 2)
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals(ground_truth[element_one.id_in_frame],
element_two.id_in_frame)
plt.close('all')
def test_track_special_case_seven(self):
"""generate a random mesh, copy it, perform a death event, and find maximum common subgraph
not sure whether this one even works!
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.load(
path.join(dirname(__file__), 'data',
'special_death_mesh_seven.mesh'))
mesh_two = mesh.load(
path.join(dirname(__file__), 'data',
'special_death_mesh_seven.mesh'))
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_in_reverse_order()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[
element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
mesh_two.kill_element_with_frame_id(most_central_element.id_in_frame)
tracked_ids = tracking.track(mesh_one, mesh_two)
# subgraph_finder = tracking.ReducedBacktrackingSubgraphFinder(mesh_one, mesh_two)
# subgraph_finder.find_maximum_common_subgraph()
#
# largest_mappings = subgraph_finder.largest_mappings
#
# for mapping_index, large_mapping in enumerate(largest_mappings):
#
# tracked_ids = []
#
# for element_one in mesh_one.elements:
# element_one.global_id = None
#
# for element_two in mesh_two.elements:
# element_two.global_id = None
#
# for global_id, frame_one_id in enumerate(large_mapping):
# mesh_one.get_element_with_frame_id(frame_one_id).global_id = global_id
# mesh_two.get_element_with_frame_id(large_mapping[frame_one_id]).global_id = global_id
# tracked_ids.append(global_id)
#
# mesh_one.index_global_ids()
# mesh_two.index_global_ids()
#
# mesh_one.plot('mesh_special_before_death_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
# mesh_two.plot('mesh_special_after_death_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
mesh_one.plot(path.join(dirname(__file__), 'output',
'special_tracked_mesh_7_before_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
mesh_two.plot(path.join(dirname(__file__), 'output',
'special_tracked_mesh_7_after_death.pdf'),
color_by_global_id=True,
total_number_of_global_ids=len(tracked_ids))
dangling_elements_one = mesh_one.get_dangling_element_ids(
ground_truth.keys())
self.assertGreaterEqual(
len(tracked_ids),
max(mesh_one.get_num_elements() - 4,
mesh_one.get_num_elements() - len(dangling_elements_one) - 1))
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals(ground_truth[element_one.id_in_frame],
element_two.id_in_frame)
plt.close('all')
def make_double_division_plot():
"""We load a mesh where two maximum common subgraphs will be identified, and track the division event"""
mesh_one = mesh.creation.generate_random_tesselation(9, 9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[
element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# pick the element closest to the centre
most_central_element = mesh_two.find_most_central_element()
# get adjacent element ids
adjacent_elements = most_central_element.get_ids_of_adjacent_elements()
# pick one
second_dividing_cell = adjacent_elements[0]
mesh_two.divide_element_with_frame_id(most_central_element.id_in_frame)
mesh_two.divide_element_with_frame_id(second_dividing_cell)
tracked_ids = tracking.track(mesh_one, mesh_two)
plotname = 'double_division'
figuresize = (4, 2.75)
figure_1 = plt.figure(figsize=figuresize)
first_polygon_collection = mesh_one.get_polygon_collection(
color_by_global_id=True, total_number_of_global_ids=len(tracked_ids))
figure_1.gca().add_collection(first_polygon_collection)
figure_1.gca().set_aspect('equal')
figure_1.gca().autoscale_view()
plt.axis('off')
this_filename = plotname + '_before_all_colors.pdf'
figure_1.savefig(this_filename, bbox_inches='tight')
plt.close(figure_1)
figure_2 = plt.figure(figsize=figuresize)
second_polygon_collection = mesh_two.get_polygon_collection(
color_by_global_id=True, total_number_of_global_ids=len(tracked_ids))
figure_2.gca().add_collection(second_polygon_collection)
figure_2.gca().set_aspect('equal')
figure_2.gca().autoscale_view()
plt.axis('off')
this_filename = plotname + '_after_all_colors.pdf'
figure_2.savefig(this_filename, bbox_inches='tight')
plt.close(figure_2)
figure_3 = plt.figure(figsize=figuresize)
third_polygon_collection = mesh_one.get_polygon_collection(
color_by_global_id=True, total_number_of_global_ids=len(tracked_ids))
polygon_list = []
for element in mesh_one.elements:
this_polygon = mpl.patches.Polygon(
[node.position for node in element.nodes], fill=True)
if element.global_id == None:
this_polygon.set_facecolor([1.0, 1.0, 1.0])
else:
if element.id_in_frame in ground_truth:
second_element = mesh_two.get_element_with_global_id(
element.global_id).id_in_frame
if ground_truth[element.id_in_frame] == second_element:
this_polygon.set_facecolor('#2dec34')
else:
this_polygon.set_facecolor('red')
else:
this_polygon.set_facecolor('red')
polygon_list.append(this_polygon)
third_polygon_collection = mpl.collections.PatchCollection(
polygon_list, match_original=True)
figure_3.gca().add_collection(third_polygon_collection)
figure_3.gca().set_aspect('equal')
figure_3.gca().autoscale_view()
plt.axis('off')
this_filename = plotname + '_before.pdf'
figure_3.savefig(this_filename, bbox_inches='tight')
plt.close(figure_3)
figure_4 = plt.figure(figsize=figuresize)
fourth_polygon_collection = mesh_two.get_polygon_collection(
color_by_global_id=True, total_number_of_global_ids=len(tracked_ids))
polygon_list = []
for element in mesh_two.elements:
this_polygon = mpl.patches.Polygon(
[node.position for node in element.nodes], fill=True)
if element.global_id == None:
this_polygon.set_facecolor([1.0, 1.0, 1.0])
else:
if element.id_in_frame in ground_truth.values():
first_element = mesh_one.get_element_with_global_id(
element.global_id).id_in_frame
if first_element in ground_truth:
if ground_truth[first_element] == element.id_in_frame:
this_polygon.set_facecolor('#2dec34')
else:
this_polygon.set_facecolor('red')
else:
this_polygon.set_facecolor('red')
else:
this_polygon.set_facecolor('red')
polygon_list.append(this_polygon)
fourth_polygon_collection = mpl.collections.PatchCollection(
polygon_list, match_original=True)
figure_4.gca().add_collection(fourth_polygon_collection)
figure_4.gca().set_aspect('equal')
figure_4.gca().autoscale_view()
plt.axis('off')
this_filename = plotname + '_after.pdf'
figure_4.savefig(this_filename, bbox_inches='tight')
plt.close(figure_4)
def test_track_special_t1_swap_4(self):
"""generate a random mesh, copy it, perform a t1 swap on it, and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.load(path.join(dirname(__file__), 'data', 'special_t1_mesh_four.mesh'))
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# Perform T1 swap on mesh two
# First pick a node in the centre
mesh_centre = mesh_two.calculate_centre()
# pick the node closest to the centre
min_distance = 3*mesh_two.calculate_height()
for node in mesh_two.nodes:
distance = np.linalg.norm(node.position - mesh_centre)
if distance < min_distance:
min_distance = distance
most_central_node = node
# pick a node that shares an edge with this central node
for local_index, element_node in enumerate(most_central_node.adjacent_elements[0].nodes):
if element_node.id == most_central_node.id:
num_nodes_this_element = most_central_node.adjacent_elements[0].get_num_nodes()
one_edge_node = most_central_node.adjacent_elements[0].nodes[(local_index+1)%num_nodes_this_element]
break
mesh_two.perform_t1_swap( most_central_node.id, one_edge_node.id )
tracked_ids = tracking.track( mesh_one, mesh_two )
# subgraph_finder = tracking.LocalisedSubgraphFinder(mesh_one, mesh_two)
# subgraph_finder.find_maximum_common_subgraph()
# post_processor = tracking.PostProcessor(mesh_one, mesh_two, subgraph_finder.largest_mappings)
# post_processor.tidy_current_mapping()
# post_processor.index_global_ids_from_largest_mappings()
# network_one = mesh_one.generate_network_of_unidentified_elements()
# print network_one.nodes()
# post_processor.altered_fill_in_by_adjacency(network_one)
# post_processor.index_global_ids()
# subgraph_finder = tracking.LocalisedSubgraphFinder(mesh_one, mesh_two)
# subgraph_finder.find_maximum_common_subgraph()
# largest_mappings = subgraph_finder.largest_mappings
#
# for mapping_index, large_mapping in enumerate(largest_mappings):
#
# tracked_ids = []
#
# for element_one in mesh_one.elements:
# element_one.global_id = None
#
# for element_two in mesh_two.elements:
# element_two.global_id = None
#
# for global_id, frame_one_id in enumerate(large_mapping):
# mesh_one.get_element_with_frame_id(frame_one_id).global_id = global_id
# mesh_two.get_element_with_frame_id(large_mapping[frame_one_id]).global_id = global_id
# tracked_ids.append(global_id)
#
# mesh_one.index_global_ids()
# mesh_two.index_global_ids()
#
# mesh_one.plot('mesh_special_before_division_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
# mesh_two.plot('mesh_special_after_division_' + str(mapping_index) + '.pdf', color_by_global_id = True,
# total_number_of_global_ids = len( tracked_ids ) )
#
mesh_one.plot(path.join(dirname(__file__),'output','tracked_mesh_before_special_t1_swap_four.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements() )
mesh_two.plot(path.join(dirname(__file__),'output','tracked_mesh_after_special_t1_swap_four.pdf'), color_by_global_id = True,
total_number_of_global_ids = mesh_one.get_num_elements() )
# # make sure that the entire mesh was tracked
# self.assertEqual( len(tracked_ids), mesh_one.get_num_elements() )
# mesh_one.plot(path.join(dirname(__file__),'output','tracked_mesh_before_special_t1_swap_three.pdf'))
# mesh_two.plot(path.join(dirname(__file__),'output','tracked_mesh_after_special_t1_swap_three.pdf'))
#
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals( ground_truth[element_one.id_in_frame], element_two.id_in_frame )
plt.close('all')
def xest_track_t1_swap(self):
"""generate a random mesh, copy it, perform a t1 swap on it, and track it.
"""
sys.setrecursionlimit(40000)
mesh_one = mesh.creation.generate_random_tesselation(9,9)
mesh_two = copy.deepcopy(mesh_one)
mesh_one.assign_frame_ids_in_order()
mesh_two.assign_frame_ids_randomly()
mesh_one.save(path.join(dirname(__file__),'output','mesh_t1_one.mesh'))
mesh_one.save(path.join(dirname(__file__),'output','mesh_t1_two.mesh'))
# build ground truth for testing the mapping
ground_truth = {}
for element_index, element in enumerate(mesh_one.elements):
ground_truth[element.id_in_frame] = mesh_two.elements[element_index].id_in_frame
# Perform T1 swap on mesh two
# First pick a node in the centre
mesh_centre = mesh_two.calculate_centre()
# pick the node closest to the centre
min_distance = 3*mesh_two.calculate_height()
for node in mesh_two.nodes:
distance = np.linalg.norm(node.position - mesh_centre)
if distance < min_distance:
min_distance = distance
most_central_node = node
# pick a node that shares an edge with this central node
for local_index, element_node in enumerate(most_central_node.adjacent_elements[0].nodes):
if element_node.id == most_central_node.id:
num_nodes_this_element = most_central_node.adjacent_elements[0].get_num_nodes()
one_edge_node = most_central_node.adjacent_elements[0].nodes[(local_index+1)%num_nodes_this_element]
break
mesh_two.perform_t1_swap( most_central_node.id, one_edge_node.id )
mesh_one.plot(path.join(dirname(__file__),'output','tracked_mesh_before_t1_swap.pdf'))
mesh_two.plot(path.join(dirname(__file__),'output','tracked_mesh_after_t1_swap.pdf'))
tracked_ids = tracking.track( mesh_one, mesh_two )
mesh_one.plot(path.join(dirname(__file__),'output','tracked_mesh_before_t1_swap.pdf'), color_by_global_id = True,
total_number_of_global_ids = len(tracked_ids) )
mesh_two.plot(path.join(dirname(__file__),'output','tracked_mesh_after_t1_swap.pdf'), color_by_global_id = True,
total_number_of_global_ids = len(tracked_ids) )
# make sure that the entire mesh was tracked
dangling_elements_one = mesh_one.get_dangling_element_ids(ground_truth.keys())
self.assertGreaterEqual(len(tracked_ids),
max(mesh_one.get_num_elements() - 3,
mesh_one.get_num_elements() - len(dangling_elements_one)))
for global_id in tracked_ids:
# and that the mapping coincides with the ground truth for all tracked ids
element_one = mesh_one.get_element_with_global_id(global_id)
element_two = mesh_two.get_element_with_global_id(global_id)
self.assertEquals( ground_truth[element_one.id_in_frame], element_two.id_in_frame )
plt.close('all')
channel[7].codePhase = 26519
channel[7].status = 'T'
showChannelStatus(channel, settings)
#Track the acquired satellites
trackSamples = getSamples.int8(
settings.fileName, settings.msToProcess, 11 * samplesPerCode
) #11*samplesPerCode is number of samples used in acquisition
if settings.skipTracking:
print "\nLoading old tracking results ... ",
(trackResults, channel) = pickle.load(open("trackResults.pickle", "rb"))
print "done"
else:
startTime = datetime.now()
print "\nTracking started at", startTime
(trackResults, channel) = track(trackSamples, channel, settings)
pickle.dump((trackResults, channel), open("trackResults.pickle", "wb"))
print "Tracking Done. Elapsed time =", (datetime.now() - startTime)
if settings.plotTrackingLow:
trackLowFigures = plotTrackingLow(trackResults, settings)
if settings.plotTrackingHigh:
trackHighFigure = plotTrackingHigh(channel, trackResults, settings)
#Do navigation
if settings.skipNavigation:
print "\nLoading old navigation results ... ",
(navSolutions, eph) = pickle.load(open("navResults.pickle", "rb"))
print "done"
else:
startTime = datetime.now()
print "\nNavigation started at", startTime