class Budget(object):
"""Device budget (for lack of a better term)
Details
-------
Keeps a semaphore for the total number of resources available,
and a device-specific atomic counter of available slots.
"""
def __init__(self, devices, n_per_device):
self.devices, self.n_per_device = devices, n_per_device
self.total = Semaphore(len(devices) * n_per_device)
self.alloc = Array("i", len(devices) * [n_per_device])
def acquire(self):
self.total.acquire()
with self.alloc.get_lock():
# get the largest counter
index = max(range(len(self.alloc)), key=self.alloc.__getitem__)
# assert self.alloc[index] > 0
# acquire the index and decrease the counter
self.alloc[index] -= 1
return index
def release(self, index):
with self.alloc.get_lock():
self.alloc[index] += 1
self.total.release()
def __getitem__(self, index):
return self.devices[index]
class MpSafeSharedArray:
"""Multiprocessing-safe shared array."""
DTYPE_TO_CTYPE = {
np.int: ctypes.c_long,
np.bool: ctypes.c_bool,
np.float: ctypes.c_double
}
def __init__(self, shape, dtype=np.float):
warnings.warn(
'MpSafeSharedArray is experimental. Use at your own risk.')
if dtype not in MpSafeSharedArray.DTYPE_TO_CTYPE:
raise ValueError('Unsupported dtype')
self._shape = shape
self._dtype = dtype
ctype = MpSafeSharedArray.DTYPE_TO_CTYPE[dtype]
num_elements = reduce(lambda x, y: x * y, shape)
self._mp_arr = Array(ctype, num_elements)
def get_lock(self):
return self._mp_arr.get_lock()
def get_array(self):
buffer = self._mp_arr.get_obj()
arr = np.ndarray(shape=self._shape, dtype=self._dtype, buffer=buffer)
return arr
def bestMoveConcurrent(self):
start = time.time()
corners = [
0, self.board.size - 1,
(self.board.size * self.board.size) - self.board.size,
(self.board.size * self.board.size) - 1
]
if self.board.getMoveCount() == 1 and self.board.board[
self.board.size // 2][self.board.size // 2] != str(
(self.board.size * self.board.size) // 2):
# print("Total number of comparisons " + str(self.totalComp))
# print("Total time taken: " + str(time.time() - start))
return random.choice(corners)
bestValueSingle = Value(ctypes.c_long,
1000000 if self.playerIsFirst else -1000000)
counter = Value(ctypes.c_int, 0)
bestMovesArray = Array(
ctypes.c_int, range(self.board.getSize() * self.board.getSize()))
threads = []
totalComp = Value(ctypes.c_int, 0)
stop = [False]
row = 0
while (not stop[0] and row < self.board.size):
col = 0
while (not stop[0] and col < self.board.size):
if (self.board.isCellEmpty(row, col)):
threads.append(
Process(target=self.callMinimaxConcurrent,
args=(row, col, self.board.clone(), 0,
self.maxDepth, self.playerIsFirst,
-1000000, 1000000, counter,
bestMovesArray, bestValueSingle,
totalComp, stop)))
col += 1
row += 1
# print("Total number of threads " + str(len(threads)))
for thread in threads:
thread.start()
for thread in threads:
if stop[0]:
for thread in threads:
thread.terminate()
else:
thread.join()
with counter.get_lock():
with bestMovesArray.get_lock():
# print("This is the best move " + str(bestMovesArray[0]))
# print("Total number of comparisons " + str(totalComp.value))
# print("Total time taken: " + str(time.time() - start))
if (counter.value > 0):
return random.choice(bestMovesArray[:counter.value])
return bestMovesArray[0]
class pos():
def __init__(self):
xpos = np.zeros(MEMORYDEPTH * NUMBOTS, dtype=np.int16, order="C")
ypos = np.zeros(MEMORYDEPTH * NUMBOTS, dtype=np.int16, order="C")
self.ids = np.zeros(NUMBOTS, dtype=np.int16, order="C")
self.xpos = Array('I', xpos)
self.ypos = Array('I', ypos)
self.latest = Value('I', 0, lock=True)
self.cap = cv2.VideoCapture(0)
self.iter = 0
def updatepos(self):
while True:
ret, frame = self.cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
with self.latest.get_lock():
self.latest.value = 5
with self.xpos.get_lock():
self.xpos[self.iter % NUMBOTS] = self.iter
with self.ypos.get_lock():
self.ypos[self.iter % NUMBOTS] = self.iter
self.iter += 1
def display_image(array_a: mp.Array, event_start: mp.Event,
event_quit: mp.Event, event_next_img: mp.Event,
width: mp.Value, height: mp.Value):
"""
Continually reads from array_a & displays image w/ OpenCV.imshow()
Waits for <q> key press to close window or <ENTER> to display next image
- array_a: shared memory that contains single image to display
- event_start: event signal to indicate when array_a has an image
- event_quit: event signal to stop upon shutdown
- event_next_img: event signal to display next image
- width: image width (in pixels)
- height: image height (in pixels)
Return values: None
"""
# TODO: get rid of this, I feel like I could make due with fewer event signals...
event_start.wait() # waits/blocks until array_a has an image
while not event_quit.is_set():
with array_a.get_lock():
# reads image from array_a as np.ndarray with C type unsigned int
image = np.frombuffer(array_a.get_obj(),
dtype="I").reshape(height.value, width.value,
3)
color_text = RGB_COLORS[tuple(image[0][0])]
# converts RGB image to BGR for OpenCV and displays image in new window
cv2.imshow(f"Random Color Image Viewer",
cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_BGR2RGB))
print(f"Image viewer showing: {color_text}")
print(f"Press <Enter> to view next image or 'q' to quit...")
key = cv2.waitKey(0)
if key == ord('q'): # if 'q' is pressed, quit
event_quit.set()
event_next_img.set()
break
elif key == 13: # if <ENTER> key is pressed, go to next image
event_next_img.set()
print("\n*********\n <Enter> key pressed \n*********\n")
# TODO: eliminate this sleep function!
time.sleep(
0.01
) # Atm, necessary to block to synchronize with other process.
def run(frame: Array, target_in_sight: Condition):
archive_path = Path("/mnt/nas/data/birdthings")
archive_path.mkdir(exist_ok=True, parents=True)
while True:
with target_in_sight:
target_in_sight.wait()
with frame.get_lock():
now = datetime.now()
if not (7 < now.hour < 18):
continue
datepart, timepart = str(now).split(" ")
dest = (
archive_path / datepart / timepart.split(":")[0] / (timepart + ".jpeg")
)
dest.parent.mkdir(exist_ok=True, parents=True)
Image.frombytes("RGB", camera.RESOLUTION, frame.get_obj()).save(
dest, format="jpeg"
)
logging.info(f'archived image {dest}')
def run(frame: Array, new_frame: Condition):
with picamera.PiCamera(
resolution=RESOLUTION) as camera, picamera.array.PiRGBArray(
camera, size=RESOLUTION) as data_container:
stream = camera.capture_continuous(data_container,
format="rgb",
use_video_port=True)
f: picamera.array.PiArrayOutput
for f in stream:
with frame.get_lock():
image = numpy.frombuffer(frame.get_obj(),
dtype=numpy.uint8).reshape(
(RESOLUTION[1], RESOLUTION[0], 3))
numpy.copyto(image, f.array)
with new_frame:
new_frame.notify_all()
data_container.seek(0)
data_container.truncate()
class GridMapper(Process):
def __init__(self, params: GridMapperParams) -> None:
super().__init__()
self.__params = self.__params_type_checked(params)
self.__stop = Stop()
self.__output = Array('d', self.__params.grid.size)
self.__kde = KernelDensity(bandwidth=self.__params.kernel.bandwidth,
kernel=self.__params.kernel.name,
**KDE_PARAMETERS)
self.__grid = self.__grid_from_params()
@property
def stop(self):
return self.__stop
@property
def output(self) -> ARRAY:
return self.__output
def run(self) -> None:
while not self.__stop.is_set():
if self.__params.data:
n_points = len(self.__params.data)
self.__kde.fit(self.__params.data.values())
density_on_grid = exp(self.__kde.score_samples(self.__grid))
with self.__output.get_lock():
self.__output.get_obj()[:] = n_points * density_on_grid
def __grid_from_params(self) -> ndarray:
x_line = linspace(*self.__params.bounds.x_range, self.__params.grid.x)
y_line = linspace(*self.__params.bounds.y_range, self.__params.grid.y)
x_grid, y_grid = meshgrid(x_line, y_line)
return column_stack((x_grid.ravel(), y_grid.ravel()))
@staticmethod
def __params_type_checked(value: GridMapperParams) -> GridMapperParams:
if type(value) is not GridMapperParams:
raise TypeError('Parameters must be of type <GridMapperParams>!')
return value
class AstractProcessCamera:
'''
polling the camera in separate process
'''
def __init__(self, width, height, framerate):
self.width = width
self.height = height
self.framerate = framerate
self.is_running = Event()
self.is_running.set()
self._shared_array = Array(ctypes.c_uint8, [0] * (width * height * 3))
self._image = self.get_numpy_array(self._shared_array, self.width,
self.height)
# fill with zeros
self._image[:] = np.zeros((self.height, self.width, 3), dtype=np.uint8)
self._process = Process(target=self.update,
args=(self.is_running, self._shared_array,
self.width, self.height, self.framerate))
self._process.start()
@classmethod
def get_numpy_array(cls, shared_array, width, height):
shared_numpy_array = np.frombuffer(shared_array.get_obj(),
dtype=np.uint8)
return shared_numpy_array.reshape((height, width, 3))
@classmethod
def update(cls, is_running, shared_array, width, height, framerate):
raise NotImplementedError
def read(self):
with self._shared_array.get_lock():
return self._image.copy()
def release(self):
self.is_running.clear()
self._process.join()
class FFMpegVideoSource():
def __init__(self):
image_size = (IMAGE_WIDTH, IMAGE_HEIGHT, COLOR_CHANNELS)
arr_size = IMAGE_WIDTH * IMAGE_HEIGHT * COLOR_CHANNELS
self._shared_arr = Array(ctypes.c_uint8, arr_size)
self._image_outside_thread = np.frombuffer(self._shared_arr.get_obj(),
dtype=np.uint8)
self._image_outside_thread = np.reshape(self._image_outside_thread,
image_size)
self._p = Process(target=self._run,
args=(self._shared_arr, image_size, URL))
self._p.daemon = True
self._p.start()
def _crop_center(self, image, cropped_width, cropped_height):
height, width, _ = image.shape
startx = int((width - cropped_width) / 2)
starty = int((height - cropped_height) / 2)
stopx = startx + cropped_width
stopy = starty + cropped_height
image = image[starty:stopy, startx:stopx, :]
return image
def _resize(self, image, width, height):
return cv2.resize(image, (width, height))
def frame(self):
"""
Get Frame
Returns : numpy.array(int8)
Image as a numpy array
"""
with self._shared_arr.get_lock():
return np.copy(self._image_outside_thread)
def frame_available(self):
"""
Check if frame is available
Returns : boolean
true if frame is available otherwise false
"""
with self._shared_arr.get_lock():
available = not isinstance(self._image_outside_thread, type(None))
return available
def stop(self):
self._p.terminate()
def _run(self, shared_array, image_size, url):
"""
Get frame to update _frame
"""
try:
image_inside_thread = np.frombuffer(shared_array.get_obj(),
dtype=np.uint8)
image_inside_thread = np.reshape(image_inside_thread, image_size)
cap = cv2.VideoCapture(url)
while True:
ret, frame = cap.read()
if not ret:
break
if frame is None:
print(f'No image from {url}')
continue
with shared_array.get_lock():
image_inside_thread[:] = frame
except Exception as error:
print(f'Got unexpected exception in "main" Message: {error}')
class PointRelaxer():
def __init__(self):
self.n_relaxation_workers = 8
# self.points_array = None
# self.work_array = None
self.cancellation = Value('i', 0, lock=True)
self.relax_var = Value('i', 0, lock=True)
self.relax_completed_var = Value('i', 0, lock=True)
self.n_points = Value('i', 0, lock=False)
self.points_io_var = Value('i', 0, lock=False)
self._buffer_size = None
self.neighors_array_buffer_multiplier = 4
self.points = None
self.points_relaxed = None
self.points_io = None
self.neighbor_divs = None
self.neighbors = None
self.delaunay_process = None
self.relax_processes = []
self.alpha = Value('f', 0.1, lock=True)
self.beta = Value('f', 0.04, lock=True)
def init_processes(self, buffer_size):
self._buffer_size = buffer_size
if self.points:
del self.points
if self.points_relaxed:
del self.points_relaxed
if self.points_io:
del self.points_io
if self.neighbor_divs:
del self.neighbor_divs
if self.neighbors:
del self.neighbors
n_neighbors = self.neighors_array_buffer_multiplier * buffer_size
self.points = Array(Vector2, buffer_size, lock=False)
self.points_relaxed = Array(Vector2, buffer_size, lock=False)
self.points_io = Array(Vector2, buffer_size, lock=True)
self.neighbor_divs = Array(c_long, buffer_size + 1, lock=False)
self.neighbors = Array(c_long, n_neighbors, lock=False)
args_common = (self.cancellation, self.relax_var,
self.relax_completed_var, self.n_points, self.points,
self.points_relaxed, self.neighbor_divs, self.neighbors)
d_args = (self.n_relaxation_workers, self.points_io,
self.points_io_var) + args_common
r_args_suffix = (self.n_relaxation_workers, self.alpha, self.beta) + \
args_common
self.delaunay_process = Process(target=delaunay_loop, args=d_args)
self.relax_processes = [
Process(target=relax_points_loop, args=(i, ) + r_args_suffix)
for i in range(self.n_relaxation_workers)
]
def set_points(self, points):
with self.points_io.get_lock():
n_points = len(points)
for idx in range(n_points):
p = points[idx]
# Dithering prevents issues with Delaunay calculation
r = 0.00001 * np.random.rand(2)
p = (p[0] + r[0], p[1] + r[1])
self.points_io[idx] = tuple(p)
self.n_points.value = n_points
self.points_io_var.value = 1
def get_points(self):
with self.points_io.get_lock():
return [tuple(self.points[i]) for i in range(self.n_points.value)]
def start_all(self):
self.delaunay_process.start()
for r in self.relax_processes:
r.start()
def stop_all(self):
with self.cancellation.get_lock():
self.cancellation.value = 1
if self.delaunay_process:
self.delaunay_process.join()
for r in self.relax_processes:
r.join()
with self.cancellation.get_lock():
self.cancellation.value = 0
def _biderectional_dijkstra_branch(adj_list: list,
sink: int,
to_visit: PriorityQueue,
visited_costs: Array,
visited_prev_nodes: Array,
prospect: Array,
priorityq_top: Array,
kill: Event,
failed: Hashable = None,
sync: tuple = None):
"""The target function for either the forward or the reverse search process.
Args:
adj_list (list) : the adjacency list
sink (int) : the source or the spur-node, if it is the
reverse search
to_visit (PriorityQueue) : the PriorityQueue
visited_costs (Array) : column major packed costs of both searches
visited_prev_nodes (Array) : column major packed prev nodes of the searches
prospect (Array) : see bidirectional Dijkstra termination
priorityq_top (Array) : the top values of both PriorityQueue's
kill (Event) : flag to notify the other process to finish
failed (hashable) : the failed node
sync (tuple) : 2 Event's to synchronize the two searches
"""
# visited_costs and visited_prev_nodes are a single vector shared by both
# searches; thus, each search has to work with the proper slice.
n = len(adj_list) - 1
is_forward, visited_offset, opposite_visited_offset = _visited_offsets(n)
# Force the synchronization of the processes.
sync[int(not is_forward)].set()
sync[int(is_forward)].wait()
while to_visit:
u_path_cost, u_prev, u = to_visit.pop_low()
if u == failed:
continue
# -1 denotes an unconnected node and, in that case, node and previous node
# are the same by initialization.
with visited_costs.get_lock():
if u_path_cost == math.inf:
visited_costs[u + visited_offset] = -1
continue
visited_costs[u + visited_offset] = u_path_cost
with visited_prev_nodes.get_lock():
visited_prev_nodes[u + visited_offset] = u_prev
if (kill.is_set()) or (u == sink):
kill.set()
return
for v, uv_weight in adj_list[u]:
if v == failed:
continue
if v in to_visit:
# Check if v is visited by the other process and, if yes, construct the
# prospect path.
with visited_prev_nodes.get_lock():
if ((visited_prev_nodes[v + opposite_visited_offset] != v)
and
(visited_costs[v + opposite_visited_offset] != 0)):
# print(f"{current_process().name}: u: {u} v: {v}"
# f" v visted from:"
# f" {visited_prev_nodes[v + opposite_visited_offset]}")
uv_prospect_cost = (
u_path_cost + uv_weight +
visited_costs[v + opposite_visited_offset])
with prospect.get_lock():
if (uv_prospect_cost <
prospect[0]) or (sum(prospect) == 0):
# then this is the shortest prospect yet or the 1st one.
prospect[0] = uv_prospect_cost
prospect[3] = uv_weight
if is_forward:
prospect[1] = u
prospect[2] = v
else:
prospect[1] = v
prospect[2] = u
# print(f"{current_process().name}: {prospect[0]}"
# f" {prospect[1]} {prospect[2]}\n")
to_visit.relax_priority([u_path_cost + uv_weight, u, v])
# Termination condition
pq_top = to_visit.peek()[0]
if pq_top == math.inf:
pq_top = 0
# print(f"{current_process().name}: prospect[0]: {prospect[0]}"
# f" topf+topr: {priorityq_top[0]} + {priorityq_top[1]}")
with prospect.get_lock():
with priorityq_top.get_lock():
priorityq_top[int(not is_forward)] = pq_top
if (sum(priorityq_top) >= prospect[0] != 0) or (kill.is_set()):
kill.set()
return
def acquire_parallel(self, worker_cls, worker_args, result_shape, plot=False):
"""
:param worker: Function which the subordinate threads execute as their target
:param proc_fun: Function used by the subordinate threads to process their buffers
:param result_shape: Shape of the buffer which is the result of the entire acquisition.
"""
from multiprocessing import Array, Value, Event
from slab.plotting import ScriptPlotter
import time
acquire_buffer_time = self.samples_per_buffer / (self.samples_per_second)
print('Acquire buffer time %.2e' % acquire_buffer_time)
print('Inter-buffer time %.2e' % self.seconds_per_buffer)
print('Duty Cycle', acquire_buffer_time / self.seconds_per_buffer)
try:
# I don't know why this needs to happen again?
channel = 0
if self.ch1_enabled:
channel |= 1
if self.ch2_enabled:
channel |= 2
pretriggers = C.c_long(0)
flags = U32(513)
ret = self.Az.AlazarBeforeAsyncRead(self.handle,U32(channel),pretriggers,
U32(self.config.samplesPerRecord),
U32(self.config.recordsPerBuffer),
U32(self.config.recordsPerAcquisition),
flags)
# Initialize buffers
buffers = [Array(U8, self.bytes_per_buffer) for _ in range(self.buffer_count)]
for b in buffers:
ret = self.Az.AlazarPostAsyncBuffer(self.handle, b.get_obj(), U32(self.bytes_per_buffer))
self.assert_az(ret, 0, 'Initial Post Buffer')
res_buffer = Array(C.c_longdouble, result_shape)
# Initialize threads
bufs_merged = Value(U32, 1)
buf_ready_events = [Event() for _ in range(self.buffer_count)]
buf_post_events = [Event() for _ in range(self.buffer_count)]
workers = [worker_cls(*(worker_args + (self.config, b, bre, bpe, res_buffer, bufs_merged)))
for b, bre, bpe in zip(buffers, buf_ready_events, buf_post_events)]
for w in workers:
w.start()
time.sleep(1)
import atexit
atexit.register(lambda: [w.terminate() for w in workers])
# Initialize things used during capture
if plot:
plotter = ScriptPlotter()
plotter.init_plot('Data', rank=1, accum=False)
buffers_acquired, buffers_completed, plot_count = 0, 0, 0
start_time = time.time()
# Begin capture
ret = self.Az.AlazarStartCapture(self.handle)
self.assert_az(ret, 0, "Start Capture")
unready_count = 0
while buffers_completed < self.buffers_per_acquisition:
# Post all completed buffers
while buf_post_events[buffers_completed % self.buffer_count].is_set():
buf_post_events[buffers_completed % self.buffer_count].clear()
buf = buffers[buffers_completed % self.buffer_count]
with buf.get_lock():
ret = self.Az.AlazarPostAsyncBuffer(self.handle, buf.get_obj(), U32(self.bytes_per_buffer))
self.assert_az(ret, buffers_acquired, 'Post Buffer')
buffers_completed += 1
# Current buffer rotates in a ring
buf_idx = buffers_acquired % self.buffer_count
buf = buffers[buf_idx]
# Pull data to buffer
with buf.get_lock():
ret = self.Az.AlazarWaitAsyncBufferComplete(self.handle, buf.get_obj(), U32(self.timeout))
if ret == 573:
unready_count += 1
continue # BufferNotReady, go back and try to post some buffers.
else:
self.assert_az(ret, buffers_acquired, 'Wait Buffer Complete')
buffers_acquired += 1
# Tell worker thread to begin processing
buf_ready_events[buf_idx].set()
# If a second has elapsed, replot the avg_buffer
if (time.time() - start_time) / self.seconds_per_plot > plot_count:
if plot:
with res_buffer.get_lock():
plotter.msg(buffers_acquired, buffers_completed, bufs_merged.value)
plotter.plot(np.frombuffer(res_buffer.get_obj()), 'Data')
plot_count += 1
else:
print(buffers_acquired, buffers_completed)
plot_count += 1
finally:
pass
# self.Az.AlazarAbortAsyncRead(self.handle)
# if buffers_completed:
# final_time = time.time()
# print 'Unready Count', unready_count
# total_time = final_time - start_time
# print 'Total time', total_time
# actual_time_per_buffer = total_time / buffers_completed
# print 'Time per buffer %.2e' % actual_time_per_buffer
# errf = lambda a, b: abs(a - b) / min(a, b)
# print 'Perceived overhead %.1f%%' % (errf(actual_time_per_buffer, seconds_per_buffer) * 100)
# else:
# print 'No buffers completed'
res = np.frombuffer(res_buffer.get_obj())
return res
c2 = pipecl2.recv() #Blocking
update_c(c1.ravel(),c2.ravel()) #########
print "Running main loop..."
while runflag:
#print uflag1.value
#print uflag2.value
dat1 = uflag1.value
dat2 = uflag2.value
frame = vs.read() #for testing
#datrecv1 = pipeul1.recv() #Blocking
#datrecv2 = pipeul2.recv() #Blocking
#if datrecv1[0] and datrecv2[0]:
if (dat1 == 2) and (dat2 ==2):
#pos3d = calc3d(datrecv2[2].ravel(),datrecv1[2].ravel()) ########
with uarray1.get_lock():
arr1 = np.frombuffer(uarray1.get_obj())
with uarray2.get_lock():
arr2 = np.frombuffer(uarray2.get_obj())
pos3d = calc3d(arr1,arr2)
#print np.asarray(pos3d)
imgpts, jac = cv2.projectPoints(np.float32([np.asarray(pos3d)]).reshape(-1,3), rvecs, tvecs, mtx, dist)
cv2.rectangle(frame,(int(imgpts[0,0,0]) - 2,int(imgpts[0,0,1]) - 2),(int(imgpts[0,0,0]) + 2 ,int(imgpts[0,0,1]) + 2),(255,0,0),1)
#elif not datrecv1[1] or not datrecv2[1]:
elif (dat1 == 0) or (dat2 ==0):
runflag = False
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print "Waiting for both processes to stop..."
def main():
with open("day23.txt", "r") as fp:
memory = dict()
for i, s in enumerate(fp.read().split(",")):
memory[i] = int(s)
# Part 1
receive_queues = [Queue() for i in range(50)]
done_queue = Queue()
def receive(index):
yield index
while True:
try:
(x, y) = receive_queues[index].get_nowait()
yield x
yield y
except Empty:
yield -1
yield -1
def send(index, program):
while True:
dest = next(program)
x = next(program)
y = next(program)
if dest == 255:
done_queue.put_nowait(y)
break
receive_queues[dest].put_nowait((x, y))
senders = [
Process(target=send, args=(i, run_program(defaultdict(lambda: 0, memory), receive(i))))
for i
in range(50)
]
for sender in senders:
sender.start()
result = done_queue.get()
for sender in senders:
sender.terminate()
print(result)
# Part 2
receive_queues = [Queue() for i in range(50)]
nat_value = Array(ctypes.c_long, 2)
waiting = Array(ctypes.c_bool, len(receive_queues))
def receive(index):
yield index
while True:
try:
(x, y) = receive_queues[index].get_nowait()
with waiting.get_lock():
waiting[index] = False
yield x
yield y
except Empty:
with waiting.get_lock():
waiting[index] = True
yield -1
yield -1
def send(index, program):
while True:
dest = next(program)
x = next(program)
y = next(program)
if dest == 255:
with nat_value.get_lock():
nat_value[0] = x
nat_value[1] = y
else:
receive_queues[dest].put_nowait((x, y))
senders = [
Process(target=send, args=(i, run_program(defaultdict(lambda: 0, memory), receive(i))))
for i
in range(50)
]
for sender in senders:
sender.start()
last_nat_y = None
while True:
sleep(0.25)
with waiting.get_lock():
all_waiting = True
for w in waiting:
all_waiting = all_waiting and waiting
if all_waiting:
with nat_value.get_lock():
receive_queues[0].put_nowait((nat_value[0], nat_value[1]))
if last_nat_y == nat_value[1]:
break
else:
last_nat_y = nat_value[1]
for sender in senders:
sender.terminate()
print(last_nat_y)
def run(
detect_input: Array,
new_detect_input: Condition,
frame: Array,
preview: Array,
new_preview: Condition,
target_offset_x: Value,
target_offset_y: Value,
track: Sequence[str],
target_in_sight: Condition,
):
interp = interpreter.Interpreter(
model_path=path.abspath(
path.join(
DATA_DIR,
"model_postprocessed_quantized_128_uint8_edgetpu.tflite")),
experimental_delegates=[
tensorflow.lite.experimental.load_delegate("libedgetpu.so.1")
],
)
interp.allocate_tensors()
input_details = interp.get_input_details()
output_details = interp.get_output_details()
label_idxs = label_to_category_index(track)
while True:
with new_detect_input:
new_detect_input.wait()
with detect_input.get_lock():
input = numpy.asarray(detect_input.get_obj()).reshape(
(RESOLUTION[1], RESOLUTION[0], 3))
input_tensor = tensorflow.convert_to_tensor(input,
dtype=tensorflow.uint8)
input_tensor = input_tensor[tensorflow.newaxis, ...]
interp.set_tensor(input_details[0]["index"], input_tensor)
interp.invoke()
box_data = tensorflow.convert_to_tensor(
interp.get_tensor(output_details[0]["index"]))
class_data = tensorflow.convert_to_tensor(
interp.get_tensor(output_details[1]["index"]))
score_data = tensorflow.convert_to_tensor(
interp.get_tensor(output_details[2]["index"]))
# num_detections = tensorflow.convert_to_tensor(
# interp.get_tensor(output_details[3]["index"])
# )
class_data = (tensorflow.squeeze(class_data, axis=[0]).numpy().astype(
numpy.int64) + 1)
box_data = tensorflow.squeeze(box_data, axis=[0]).numpy()
score_data = tensorflow.squeeze(score_data, axis=[0]).numpy()
if any(item in label_idxs for item in class_data):
tracked = ((i, x) for i, x in enumerate(class_data)
if x in label_idxs)
tracked_idxs, tracked_classes = zip(*tracked)
if any(score_data[i] > 0.6 for i in tracked_idxs):
with target_in_sight:
target_in_sight.notify_all()
idx = max(
tracked_idxs,
key=lambda i: numpy.amax(box_data[i]) - numpy.amin(box_data[i]
),
)
keypoint_x = numpy.take(box_data[idx], [1, 3]).mean()
keypoint_y = numpy.take(box_data[idx], [0, 2]).mean()
target_offset_x.value = (keypoint_x - 0.5) * FOV_ANGLE
target_offset_y.value = (keypoint_y - 0.5) * FOV_ANGLE
else:
keypoint_x = None
keypoint_y = None
target_offset_x.value = float("nan")
target_offset_y.value = float("nan")
with preview.get_lock():
preview_image = numpy.frombuffer(preview.get_obj(),
dtype=numpy.uint8).reshape(
(camera.RESOLUTION[1],
camera.RESOLUTION[0], 3))
with frame.get_lock():
frame_image = numpy.frombuffer(frame.get_obj(),
dtype=numpy.uint8).reshape(
(camera.RESOLUTION[1],
camera.RESOLUTION[0], 3))
numpy.copyto(preview_image, frame_image)
if keypoint_x is not None and keypoint_y is not None:
draw_keypoints_on_image_array(
preview_image,
numpy.array([[keypoint_y, keypoint_x]]),
use_normalized_coordinates=True,
)
visualize_boxes_and_labels_on_image_array(
preview_image,
box_data,
class_data,
score_data,
LABEL_MAP,
use_normalized_coordinates=True,
line_thickness=4,
min_score_thresh=0.5,
max_boxes_to_draw=3,
)
with new_preview:
new_preview.notify_all()
width = Value("i", int(width))
if num_images.value < 1 or height.value < 1 or width.value < 1:
raise Exception
input_is_int = True
except:
print("Please input integers greater than zero for these values")
print("Press the 'q' key to quit")
array_a_size = height.value * width.value * 3
array_a = Array(ctypes.c_double, array_a_size)
quit_event = Event()
p1 = Process(target=process_one, args=(queue_a, ))
p2 = Process(target=process_two, args=(queue_a, queue_b, quit_event))
p3 = Process(target=process_three, args=(array_a, quit_event))
p1.start()
p2.start()
p3.start()
while not quit_event.is_set():
im = queue_b.get()
if im is None: break
with array_a.get_lock():
window = np.frombuffer(array_a.get_obj()).reshape(
width.value, height.value, 3)
window[:] = im
cv2.destroyAllWindows()
p1.join()
p2.join()
p3.join()
class RenderProcess:
"""
Wraps a multiprocessing.Process for rendering. Assumes there
is one MjSim per process.
"""
def __init__(self, device_id, setup_sim, update_sim, output_var_shape):
"""
Args:
- device_id (int): GPU device to use for rendering (0-indexed)
- setup_sim (callback): callback that is given a device_id and
returns a MjSim. It is responsible for making MjSim render
to given device.
- update_sim (callback): callback given a sim and device_id, and
should return a numpy array of shape `output_var_shape`.
- output_var_shape (tuple): shape of the synchronized output
array from `update_sim`.
"""
self.device_id = device_id
self.setup_sim = setup_sim
self.update_sim = update_sim
# Create a synchronized output variable (numpy array)
self._shared_output_var = Array(ctypes.c_double,
int(np.prod(output_var_shape)))
self._output_var = np.frombuffer(self._shared_output_var.get_obj())
# Number of variables used to communicate with process
self._cv = Condition()
self._ready = Value('b', 0)
self._start = Value('b', 0)
self._terminate = Value('b', 0)
# Start the actual process
self._process = Process(target=self._run)
self._process.start()
def wait(self):
""" Wait for process to be ready for another update call. """
with self._cv:
if self._start.value:
self._cv.wait()
if self._ready.value:
return
self._cv.wait()
def read(self, copy=False):
""" Reads the output variable. Returns a copy if copy=True. """
if copy:
with self._shared_output_var.get_lock():
return np.copy(self._output_var)
else:
return self._output_var
def update(self):
""" Calls update_sim asynchronously. """
with self._cv:
self._start.value = 1
self._cv.notify()
def stop(self):
""" Tells process to stop and waits for it to terminate. """
with self._cv:
self._terminate.value = 1
self._cv.notify()
self._process.join()
def _run(self):
sim = self.setup_sim(self.device_id)
while True:
with self._cv:
self._ready.value = 1
self._cv.notify_all()
with self._cv:
if not self._start.value and not self._terminate.value:
self._cv.wait()
if self._terminate.value:
break
assert self._start.value
self._start.value = 0
# Run the update and assign output variable
with self._shared_output_var.get_lock():
self._output_var[:] = self.update_sim(sim,
self.device_id).ravel()
def __init__(self, config_file: str):
with open(config_file) as file:
# Load the json configuration file
json_config = json.load(file)
# Create the different IPC message queues we will be using
self.client_mq = self.get_ipc_queue(
json_config["server"]["ipc_key_client"])
self.house_mq = self.get_ipc_queue(
json_config["server"]["ipc_key_house"])
# Create a barrier for synchronization
# 4 processes need to be synchronized : Weather, City, Market and Server Sync
# If the server_utils if configured as "auto", it runs on regular interval.
# If it's not, run when requested by the client
compute_barrier = Barrier(parties=4)
# This other barrier is used to update shared memory used for the next iteration
# of the simulation
write_barrier = Barrier(parties=4)
# Shared memory for the weather
weather_shared = Array("i", 2)
with weather_shared.get_lock():
weather_shared[0] = json_config["weather"]["temperature"]
weather_shared[1] = json_config["weather"]["cloud_coverage"]
# Shared memory for the energy price
price_shared = Value("d")
with price_shared.get_lock():
price_shared.value = json_config["market"]["initial_price"]
self.shared_variables = SharedVariables(
compute_barrier=compute_barrier,
write_barrier=write_barrier,
price_shared=price_shared,
weather_shared=weather_shared,
)
# Declaring the simulation processes
self.city = City(
shared_variables=self.shared_variables,
ipc_key_houses=json_config["server"]["ipc_key_house"],
nb_houses=json_config["cities"]["nb_houses"],
average_conso=json_config["cities"]["average_conso"],
max_prod=json_config["cities"]["max_prod"],
)
self.market = Market(
shared_variables=self.shared_variables,
politics=json_config["market"]["political_score"],
economy=json_config["market"]["economy_score"],
nb_houses=json_config["cities"]["nb_houses"],
ipc_house=json_config["server"]["ipc_key_house"],
time_interval=json_config["server"]["time_interval"],
)
self.weather = Weather(shared_variables=self.shared_variables, )
self.sync = ServerSync(
shared_variables=self.shared_variables,
time_interval=json_config["server"]["time_interval"],
)
# Starting all processes
self.city.start()
self.weather.start()
self.market.start()
self.sync.start()
signal.signal(signal.SIGINT, self.signal_handler)
print(f"{Fore.GREEN}Initialization complete{Style.RESET_ALL}")
class MainProgram:
""" Main Class of the program, initiates everything and implements OpenGL environment"""
def __init__(self):
self.init_opengl()
self.animation_clock = None
self.lost_leak = False
self.p_liquid = None
# Memory shared variables
self.q_activate, self.rst, self.lost = SimpleQueue(), SimpleQueue(), SimpleQueue()
self.liquid_grid = Array(ctypes.c_double, (Conf.dim_grille[0] + 1) * Conf.dim_grille[1])
self.liquid_im = Array(ctypes.c_double, 10 * (Conf.dim_grille[0] + 1) * 10 * Conf.dim_grille[1] * 4)
self.run_liquid_process()
# Main utility class
self.augmented_reality = AugmentedReality(Conf.width, Conf.height, self.q_activate,
self.liquid_im, self.liquid_grid)
# execute OpenGL loop forever
self.loop()
def init_opengl(self):
# OpenGL setup
glutInit(sys.argv)
glutSetOption(GLUT_ACTION_ON_WINDOW_CLOSE, GLUT_ACTION_CONTINUE_EXECUTION)
glutInitDisplayMode(GLUT_DOUBLE | GLUT_RGB | GLUT_DEPTH)
glutInitWindowSize(Conf.width, Conf.height)
glutInitWindowPosition(screen_number * 1366, 0) # main window dim + 1
glutCreateWindow("Poche AR")
glutFullScreen()
glClearColor(0.0, 0.0, 0.0, 1.0)
glutDisplayFunc(self.display)
glutReshapeFunc(self.reshape)
glutKeyboardFunc(self.keyboard)
glutIdleFunc(self.idle)
glEnable(GL_BLEND)
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA)
def run_liquid_process(self):
# Liquid control Process
self.p_liquid = Liquid(self.liquid_im, self.q_activate, self.rst, self.lost, self.liquid_grid)
self.p_liquid.daemon = True
self.p_liquid.start()
def idle(self):
""" Opengl routine function, called each loop iteration"""
Glob.delta_t = clock() - Glob.t_ref
Glob.t_ref = clock()
if Glob.mode !=2:
# update frame from webcam
self.augmented_reality.cam.take_frame()
if Glob.mode == 0:
# build mode, update bricks
self.augmented_reality.detect_brick()
self.augmented_reality.check_buttons()
if Glob.mode == 1:
# Testing structure mode
if Conf.cooling:
Conf.t_chamber = Conf.temperature if (self.augmented_reality.buttonStart.is_triggered
and self.augmented_reality.number) > 0 \
else max(Conf.t_chamber - Conf.cooling_factor * Glob.delta_t, 293)
Glob.brick_array.update(not self.augmented_reality.buttonStart.is_ready()
and self.augmented_reality.number >= 0)
else:
Glob.brick_array.update(not self.augmented_reality.buttonStart.is_ready()
and self.augmented_reality.number >= 0)
lost_struct = False # Glob.brick_array.test_loose()
if not self.lost.empty():
self.lost_leak = self.lost.get()
if (self.lost_leak or lost_struct) or self.augmented_reality.buttonReset.is_triggered:
print("reset")
if self.augmented_reality.buttonReset.is_triggered:
print("(from rst button)")
elif self.lost_leak:
print("(from liquid)")
elif lost_struct:
print("(from struct)")
self.rst.put(True)
self.augmented_reality.buttonStart.is_triggered = False
Glob.t_ref, Glob.delta_t = clock(), 0
Glob.hand_text = None
Glob.updating = False
Glob.update_timer = 0
self.augmented_reality.buttonReset.is_triggered = False
self.augmented_reality.reset()
Glob.mode = 2
self.animation_clock = clock()
self.augmented_reality.buttonStart.is_waiting = True
self.lost_leak = False
# update brick grid in liquid simulation
if Glob.brick_array is not None:
with self.liquid_grid.get_lock(): # synchronize access
arr = np.frombuffer(self.liquid_grid.get_obj()) # no data copying
arr[:Conf.dim_grille[0] * Conf.dim_grille[1]] = Glob.brick_array.get_grid().flatten()
# tell OpenGL to redraw as soon as possible
glutPostRedisplay()
def display(self):
""" Opengl drawing function, called when an update is needed"""
# Set Projection Matrix
glMatrixMode(GL_PROJECTION)
glLoadIdentity()
gluOrtho2D(0, Conf.width, 0, Conf.height)
# Switch to Model View Matrix
glMatrixMode(GL_MODELVIEW)
glLoadIdentity()
glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
self.augmented_reality.render()
if Glob.mode == 2:
# reset mode
self.augmented_reality.buttonStart.pause()
self.augmented_reality.lost_screen()
if clock() - self.animation_clock > 5:
Glob.mode = 0
else:
self.augmented_reality.buttonStart.unpause()
glutSwapBuffers()
@staticmethod
def reshape(w, h):
""" OpenGl function, change windows property when window's size changes"""
if h == 0:
h = 1
glViewport(0, 0, w, h)
glMatrixMode(GL_PROJECTION)
glLoadIdentity()
if w <= h:
glOrtho(-Glob.nRange, Glob.nRange, -Glob.nRange * h / w, Glob.nRange * h / w, -Glob.nRange, Glob.nRange)
else:
glOrtho(-Glob.nRange * w / h, Glob.nRange * w / h, -Glob.nRange, Glob.nRange, -Glob.nRange, Glob.nRange)
glMatrixMode(GL_MODELVIEW)
glLoadIdentity()
def keyboard(self, key, x, y):
""" Opengl function, add action to keyboard input"""
print("key_code =%s" % key)
if key == b'\x1b':
# kill program when escape is pressed
self.p_liquid.terminate()
self.p_liquid.join()
glutLeaveMainLoop()
if key == b'd':
# change debug mode with d key
Glob.debug = not Glob.debug
def loop(self):
""" in case we handle the loop differently """
glutMainLoop() # OpenGL loop, handle idle/display/reshape/keyboard calls
ir_values = Array('i', 6)
laser_values = Array('i', 520)
num_laser_values = Value('i', 0)
num_hall_reads = Value('i', 0)
gyro_value = Value('d', 0)
has_new_ir = Value('i', 0)
mode = Value('i', 0) # Manual, Atonomous = 0, 1
pid_cons = Array('d', 2)
pid_cons[0] = -1 # Make sure to not read pid values from array on boot
grid = Array('i', MAP_SIZE**2)
shared_pos = Array('i',2)
move_cmd = Array('c', 50)
steering_cmd_man = SimpleQueue()
# Init ir array to avoid errors in the beginning
with ir_values.get_lock():
ir_values[0] = EMPTY_TILE
# Setup and start processes
# sensor_process: Handles communication with the sensor module
# slam_process: Decision logic. Uses data recieved from both the sensor and bluetooth processes.
# The slam process also takes care of communication with the steering module.
# bluetooth_process: Handles communication with the bluetooth connected laptop
sensor_process = Process(target=sensor.sensor_serial, args=(ir_values, laser_values, gyro_value, num_laser_values, num_hall_reads, has_new_ir))
slam_process = Process(target=slam, args=(ir_values, laser_values, mode, steering_cmd_man, pid_cons, gyro_value, num_laser_values, num_hall_reads, grid, shared_pos, move_cmd, has_new_ir))
bluetooth_process = Process(target=blueztooth.bluetooth_loop, args=(ir_values, laser_values, steering_cmd_man, mode, pid_cons, num_laser_values, grid, shared_pos, move_cmd))
sensor_process.start()
slam_process.start()
bluetooth_process.start()
print("-- INIT COMPLETE --")
def main():
global top_left_icon, scale
args = get_argument()
# read all pattern images
target_dict = {}
for i in animals:
target_dict[i] = cv2.cvtColor(
cv2.imread("icons/animals/{}.png".format(animals[i])),
cv2.COLOR_BGR2GRAY)
home_screen = cv2.imread("icons/home.png")
round_start = cv2.cvtColor(cv2.imread("icons/round.png"),
cv2.COLOR_BGR2GRAY)
win = cv2.cvtColor(cv2.imread("icons/win.png"), cv2.COLOR_BGR2GRAY)
battle = cv2.cvtColor(cv2.imread("icons/battle.png"), cv2.COLOR_BGR2GRAY)
home_icons = cv2.cvtColor(cv2.imread("icons/home_icons.png"),
cv2.COLOR_BGR2GRAY)
game_mode = 0
battle_start_time = None
if args.mp:
top_left_flag = True
with mss.mss() as sct:
min_h = min_w = 300000
max_h = max_w = 0
scale = 0
print("Scan for home screen")
while True:
# Get raw pixels from the screen, save it to a Numpy array
img = np.array(sct.grab(sct.monitors[1]))
min_h, max_h, min_w, max_w, shape = locate_home_screen(
img[:, :, :3], home_screen)
if max_h != 0:
scale = img.shape[0] / shape[0]
break
try:
if scale != 0:
print("Screen detected, standing by")
game_mode = 1
min_h = int(round(min_h * scale)) - 5
max_h = int(round(max_h * scale)) + 5
min_w = int(round(min_w * scale)) - 5
max_w = int(round(max_w * scale)) + 5
coord_base = np.array([min_h, min_w])
monitor = {
"top": min_h,
"left": min_w,
"width": max_w - min_w,
"height": max_h - min_h
}
# get the correct size patterns
# round_start = cv2.resize(round_start, (0, 0), fx=scale, fy=scale)
# win = cv2.resize(win, (0, 0), fx=scale, fy=scale)
# battle = cv2.resize(battle, (0, 0), fx=scale, fy=scale)
# for i in target_dict:
# target_dict[i] = cv2.resize(target_dict[i], (0, 0), fx=scale, fy=scale)
icon_shape = np.array(
cv2.resize(target_dict[2], (0, 0), fx=scale,
fy=scale).shape)
# start second process if specified
if args.mp:
print("Start moving process...")
q = Queue(5)
shared_arr = Array(ctypes.c_double, 64)
np_arr = np.frombuffer(shared_arr.get_obj())
process_move = Process(target=move_icon,
args=(
shared_arr,
q,
icon_shape,
coord_base,
))
process_move.start()
while True:
img = np.array(sct.grab(monitor))[:, :, :3]
img = cv2.resize(img, (0, 0), fx=1 / scale, fy=1 / scale)
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
if (game_mode == 1 or game_mode == 3) and is_pattern_found(
img_gray, round_start):
game_mode = 2
battle_start_time = time.time()
print("Start battle!!!")
if args.mp:
q.put("battle")
elif game_mode == 3 and is_pattern_found(img_gray, win):
game_mode = 1
print("End battle, standing by")
if args.mp:
q.put("pause")
elif game_mode == 2:
# detect, parse, and command board
arr = get_arr(img_gray, target_dict)
if args.mp:
if top_left_icon is not None and top_left_flag:
top_left_flag = False
q.put(top_left_icon)
with shared_arr.get_lock():
np_arr[:] = arr.reshape(-1)
else:
moves = get_move(arr)
if len(moves) != 0:
for idx in range(len(moves)):
start, dd = moves[idx]
coord_start = (start * icon_shape +
(icon_shape * 2 / 3) +
top_left_icon +
coord_base).astype(np.int32)
coord_dest = (
coord_start +
dirs[dd] * icon_shape).astype(np.int32)
pyautogui.moveTo(coord_start[1],
coord_start[0])
pyautogui.dragTo(coord_dest[1],
coord_dest[0],
button='left')
# detect if cur round is over
if time.time() - battle_start_time > 29:
if is_pattern_found(img_gray, battle):
game_mode = 3
if args.mp:
q.put('pause')
print("Pause battle")
elif is_pattern_found(img_gray, home_icons):
game_mode = 1
print("Home icons detected, standing by")
elif game_mode != 1 and is_pattern_found(
img_gray, home_icons):
game_mode = 1
time.sleep(0.005)
except KeyboardInterrupt:
if args.mp:
q.put(None)
process_move.join()
class RingBuffer(object):
"""
A RingBuffer containing complex values.
"""
def __init__(self, size: int):
self.__data = Array("f", 2*size)
self.size = size
self.__left_index = Value("L", 0)
self.__right_index = Value("L", 0)
self.__length = Value("L", 0)
def __len__(self):
return self.__length.value
@property
def left_index(self):
return self.__left_index.value
@left_index.setter
def left_index(self, value):
self.__left_index.value = value % self.size
@property
def right_index(self):
return self.__right_index.value
@right_index.setter
def right_index(self, value):
self.__right_index.value = value % self.size
@property
def is_empty(self) -> bool:
return len(self) == 0
@property
def space_left(self):
return self.size - len(self)
@property
def data(self):
return np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
@property
def view_data(self):
"""
Get a representation of the ring buffer for plotting. This is expensive, so it should only be used in frontend
:return:
"""
left, right = self.left_index, self.left_index + len(self)
if left > right:
left, right = right, left
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
return np.concatenate((data[left:right], data[right:], data[:left]))
def clear(self):
self.left_index = 0
self.right_index = 0
def will_fit(self, number_values: int) -> bool:
return number_values <= self.space_left
def push(self, values: np.ndarray):
"""
Push values to buffer. If buffer can't store all values a ValueError is raised
"""
n = len(values)
if len(self) + n > self.size:
raise ValueError("Too much data to push to RingBuffer")
slide_1 = np.s_[self.right_index:min(self.right_index + n, self.size)]
slide_2 = np.s_[:max(self.right_index + n - self.size, 0)]
with self.__data.get_lock():
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
data[slide_1] = values[:slide_1.stop - slide_1.start]
data[slide_2] = values[slide_1.stop - slide_1.start:]
self.right_index += n
self.__length.value += n
def pop(self, number: int, ensure_even_length=False):
"""
Pop number of elements. If there are not enough elements, all remaining elements are returned and the
buffer is cleared afterwards. If buffer is empty, an empty numpy array is returned.
If number is -1 (or any other value below zero) than complete buffer is returned
"""
if ensure_even_length:
number -= number % 2
if len(self) == 0 or number == 0:
return np.array([], dtype=np.complex64)
if number < 0:
# take everything
number = len(self)
else:
number = min(number, len(self))
with self.__data.get_lock():
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
result = np.empty(number, dtype=np.complex64)
if self.left_index + number > len(data):
end = len(data) - self.left_index
else:
end = number
result[:end] = data[self.left_index:self.left_index + end]
if end < number:
result[end:] = data[:number-end]
self.left_index += number
self.__length.value -= number
return result
class RingBuffer(object):
"""
A RingBuffer containing complex values.
"""
def __init__(self, size: int):
self.__data = Array("f", 2 * size)
self.size = size
self.__left_index = Value("L", 0)
self.__right_index = Value("L", 0)
self.__length = Value("L", 0)
def __len__(self):
return self.__length.value
@property
def left_index(self):
return self.__left_index.value
@left_index.setter
def left_index(self, value):
self.__left_index.value = value % self.size
@property
def right_index(self):
return self.__right_index.value
@right_index.setter
def right_index(self, value):
self.__right_index.value = value % self.size
@property
def is_empty(self) -> bool:
return len(self) == 0
@property
def space_left(self):
return self.size - len(self)
@property
def data(self):
return np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
@property
def view_data(self):
"""
Get a representation of the ring buffer for plotting. This is expensive, so it should only be used in frontend
:return:
"""
left, right = self.left_index, self.left_index + len(self)
if left > right:
left, right = right, left
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
return np.concatenate((data[left:right], data[right:], data[:left]))
def clear(self):
self.left_index = 0
self.right_index = 0
def will_fit(self, number_values: int) -> bool:
return number_values <= self.space_left
def push(self, values: np.ndarray):
"""
Push values to buffer. If buffer can't store all values a ValueError is raised
"""
n = len(values)
if len(self) + n > self.size:
raise ValueError("Too much data to push to RingBuffer")
slide_1 = np.s_[self.right_index:min(self.right_index + n, self.size)]
slide_2 = np.s_[:max(self.right_index + n - self.size, 0)]
with self.__data.get_lock():
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
data[slide_1] = values[:slide_1.stop - slide_1.start]
data[slide_2] = values[slide_1.stop - slide_1.start:]
self.right_index += n
self.__length.value += n
def pop(self, number: int, ensure_even_length=False):
"""
Pop number of elements. If there are not enough elements, all remaining elements are returned and the
buffer is cleared afterwards. If buffer is empty, an empty numpy array is returned.
If number is -1 (or any other value below zero) than complete buffer is returned
"""
if ensure_even_length:
number -= number % 2
if len(self) == 0 or number == 0:
return np.array([], dtype=np.complex64)
if number < 0:
# take everything
number = len(self)
else:
number = min(number, len(self))
with self.__data.get_lock():
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
result = np.empty(number, dtype=np.complex64)
if self.left_index + number > len(data):
end = len(data) - self.left_index
else:
end = number
result[:end] = data[self.left_index:self.left_index + end]
if end < number:
result[end:] = data[:number - end]
self.left_index += number
self.__length.value -= number
return result
class VideoStream:
""" This class returns constant framerate frames from the input stream. """
def __init__(self, input_source, trg_fps, batch_size):
"""Constructor"""
try:
self._input_source = int(input_source)
except ValueError:
self._input_source = input_source
self._trg_fps = trg_fps
assert self._trg_fps > 0
self._batch_size = batch_size
assert self._batch_size > 0
cap = cv2.VideoCapture(self._input_source)
assert cap.isOpened(), "Can't open " + str(self._input_source)
source_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
source_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
cap.release()
self._image_shape = [source_height, source_width, 3]
self._batch_shape = [batch_size] + self._image_shape
self._image_buffer_size = int(np.prod(self._image_shape))
self._batch_buffer_size = int(np.prod(self._batch_shape))
self._source_finished = Value('i', False, lock=False)
self._raw_frame = Array('B', self._image_buffer_size, lock=True)
self._slow_frame = Array('B', self._image_buffer_size, lock=True)
self._slow_batch = Array('B', self._batch_buffer_size, lock=True)
self._frame_generator_process = None
self._producer_process = None
def get_live_frame(self):
"""Returns last live frame from the input stream"""
if self._source_finished.value:
return None
with self._raw_frame.get_lock():
buffer = np.frombuffer(self._raw_frame.get_obj(), dtype=np.uint8)
frame = np.copy(buffer.reshape(self._image_shape))
return frame
def get_batch(self):
"""Returns last batch of frames with constant framerate from the input stream"""
if self._source_finished.value:
return None
with self._slow_batch.get_lock():
buffer = np.frombuffer(self._slow_batch.get_obj(), dtype=np.uint8)
batch = np.copy(buffer.reshape(self._batch_shape))
return batch
def start(self):
"""Starts internal threads"""
self._frame_generator_process = \
Process(target=self._frame_generator,
args=(self._input_source, self._raw_frame, self._image_shape,
self._source_finished))
self._frame_generator_process.daemon = True
self._frame_generator_process.start()
self._producer_process = \
Process(target=self._producer,
args=(self._raw_frame, self._slow_frame, self._slow_batch,
self._trg_fps, self._batch_size, self._image_shape,
self._source_finished))
self._producer_process.daemon = True
self._producer_process.start()
def release(self):
"""Release internal threads"""
if self._frame_generator_process is not None:
self._frame_generator_process.terminate()
self._frame_generator_process.join()
if self._producer_process is not None:
self._producer_process.terminate()
self._producer_process.join()
@staticmethod
def _frame_generator(input_source, out_frame, frame_shape, finish_flag):
"""Produces live frames from the input stream"""
cap = cv2.VideoCapture(input_source)
cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
source_fps = cap.get(cv2.CAP_PROP_FPS)
if source_fps > 0:
trg_time_step = 1.0 / source_fps
else:
log.warning(
'Got a non-positive value as FPS of the input. Interpret it as 30 FPS'
)
trg_time_step = 1.0 / 30.0
while True:
start_time = time.perf_counter()
_, frame = cap.read()
if frame is None:
break
with out_frame.get_lock():
buffer = np.frombuffer(out_frame.get_obj(), dtype=np.uint8)
np.copyto(buffer.reshape(frame_shape), frame)
end_time = time.perf_counter()
elapsed_time = end_time - start_time
rest_time = trg_time_step - elapsed_time
if rest_time > 0.0:
time.sleep(rest_time)
finish_flag.value = True
cap.release()
@staticmethod
def _producer(input_frame, out_frame, out_batch, trg_fps, batch_size,
image_shape, finish_flag):
"""Produces frames and batch of frames with constant framerate
from the internal stream of frames"""
trg_time_step = 1.0 / float(trg_fps)
batch_shape = [batch_size] + image_shape
frame_buffer = []
while not finish_flag.value:
start_time = time.perf_counter()
with input_frame.get_lock():
in_frame_buffer = np.frombuffer(input_frame.get_obj(),
dtype=np.uint8)
frame = np.copy(in_frame_buffer.reshape(image_shape))
with out_frame.get_lock():
out_frame_buffer = np.frombuffer(out_frame.get_obj(),
dtype=np.uint8)
np.copyto(out_frame_buffer.reshape(image_shape), frame)
frame_buffer.append(frame)
if len(frame_buffer) > batch_size:
frame_buffer = frame_buffer[-batch_size:]
if len(frame_buffer) == batch_size:
with out_batch.get_lock():
out_batch_buffer = np.frombuffer(out_batch.get_obj(),
dtype=np.uint8)
np.copyto(out_batch_buffer.reshape(batch_shape),
frame_buffer)
end_time = time.perf_counter()
elapsed_time = end_time - start_time
rest_time = trg_time_step - elapsed_time
if rest_time > 0.0:
time.sleep(rest_time)
def acquire_parallel(self,
worker_cls,
worker_args,
result_shape,
plot=False):
"""
:param worker: Function which the subordinate threads execute as their target
:param proc_fun: Function used by the subordinate threads to process their buffers
:param result_shape: Shape of the buffer which is the result of the entire acquisition.
"""
from multiprocessing import Array, Value, Event
from slab.plotting import ScriptPlotter
import time
acquire_buffer_time = self.samples_per_buffer / (
self.samples_per_second)
print('Acquire buffer time %.2e' % acquire_buffer_time)
print('Inter-buffer time %.2e' % self.seconds_per_buffer)
print('Duty Cycle', acquire_buffer_time / self.seconds_per_buffer)
try:
# I don't know why this needs to happen again?
channel = 0
if self.ch1_enabled:
channel |= 1
if self.ch2_enabled:
channel |= 2
pretriggers = C.c_long(0)
flags = U32(513)
ret = self.Az.AlazarBeforeAsyncRead(
self.handle, U32(channel), pretriggers,
U32(self.config.samplesPerRecord),
U32(self.config.recordsPerBuffer),
U32(self.config.recordsPerAcquisition), flags)
# Initialize buffers
buffers = [
Array(U8, self.bytes_per_buffer)
for _ in range(self.buffer_count)
]
for b in buffers:
ret = self.Az.AlazarPostAsyncBuffer(self.handle, b.get_obj(),
U32(self.bytes_per_buffer))
self.assert_az(ret, 0, 'Initial Post Buffer')
res_buffer = Array(C.c_longdouble, result_shape)
# Initialize threads
bufs_merged = Value(U32, 1)
buf_ready_events = [Event() for _ in range(self.buffer_count)]
buf_post_events = [Event() for _ in range(self.buffer_count)]
workers = [
worker_cls(
*(worker_args +
(self.config, b, bre, bpe, res_buffer, bufs_merged))) for
b, bre, bpe in zip(buffers, buf_ready_events, buf_post_events)
]
for w in workers:
w.start()
time.sleep(1)
import atexit
atexit.register(lambda: [w.terminate() for w in workers])
# Initialize things used during capture
if plot:
plotter = ScriptPlotter()
plotter.init_plot('Data', rank=1, accum=False)
buffers_acquired, buffers_completed, plot_count = 0, 0, 0
start_time = time.time()
# Begin capture
ret = self.Az.AlazarStartCapture(self.handle)
self.assert_az(ret, 0, "Start Capture")
unready_count = 0
while buffers_completed < self.buffers_per_acquisition:
# Post all completed buffers
while buf_post_events[buffers_completed %
self.buffer_count].is_set():
buf_post_events[buffers_completed %
self.buffer_count].clear()
buf = buffers[buffers_completed % self.buffer_count]
with buf.get_lock():
ret = self.Az.AlazarPostAsyncBuffer(
self.handle, buf.get_obj(),
U32(self.bytes_per_buffer))
self.assert_az(ret, buffers_acquired, 'Post Buffer')
buffers_completed += 1
# Current buffer rotates in a ring
buf_idx = buffers_acquired % self.buffer_count
buf = buffers[buf_idx]
# Pull data to buffer
with buf.get_lock():
ret = self.Az.AlazarWaitAsyncBufferComplete(
self.handle, buf.get_obj(), U32(self.timeout))
if ret == 573:
unready_count += 1
continue # BufferNotReady, go back and try to post some buffers.
else:
self.assert_az(ret, buffers_acquired,
'Wait Buffer Complete')
buffers_acquired += 1
# Tell worker thread to begin processing
buf_ready_events[buf_idx].set()
# If a second has elapsed, replot the avg_buffer
if (time.time() -
start_time) / self.seconds_per_plot > plot_count:
if plot:
with res_buffer.get_lock():
plotter.msg(buffers_acquired, buffers_completed,
bufs_merged.value)
plotter.plot(np.frombuffer(res_buffer.get_obj()),
'Data')
plot_count += 1
else:
print(buffers_acquired, buffers_completed)
plot_count += 1
finally:
pass
# self.Az.AlazarAbortAsyncRead(self.handle)
# if buffers_completed:
# final_time = time.time()
# print 'Unready Count', unready_count
# total_time = final_time - start_time
# print 'Total time', total_time
# actual_time_per_buffer = total_time / buffers_completed
# print 'Time per buffer %.2e' % actual_time_per_buffer
# errf = lambda a, b: abs(a - b) / min(a, b)
# print 'Perceived overhead %.1f%%' % (errf(actual_time_per_buffer, seconds_per_buffer) * 100)
# else:
# print 'No buffers completed'
res = np.frombuffer(res_buffer.get_obj())
return res
class RingBuffer(object):
"""
A RingBuffer containing complex values.
"""
def __init__(self, size: int):
self.__data = Array("f", 2*size)
self.size = size
self.__current_index = Value("L", 0)
@property
def current_index(self):
return self.__current_index.value
@current_index.setter
def current_index(self, value):
self.__current_index.value = value
@property
def is_empty(self) -> bool:
return self.current_index == 0
@property
def space_left(self):
return self.size - self.current_index
@property
def data(self):
return np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
def __getitem__(self, index):
return self.data[index]
def __repr__(self):
return "RingBuffer " + str(self.data)
def __increase_current_index_by(self, n: int):
self.current_index += n
if self.current_index > self.size:
self.current_index = self.size
def clear(self):
self.current_index = 0
def will_fit(self, number_values: int) -> bool:
return number_values <= self.space_left
def push(self, values: np.ndarray):
"""
Push values to buffer. If buffer can't store all values a ValueError is raised
:param values:
:return:
"""
n = len(values)
with self.__data.get_lock():
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
data[self.current_index:self.current_index+n] = values
self.__increase_current_index_by(n)
def pop(self, number: int) -> np.ndarray:
"""
Pop number of elements. If there are not enough elements, all remaining elements are returned and the
buffer is cleared afterwards. If buffer is empty, an empty numpy array is returned.
"""
if number > self.current_index:
number = self.current_index
with self.__data.get_lock():
self.current_index -= number
result = np.copy(self.data[0:number])
data = np.frombuffer(self.__data.get_obj(), dtype=np.complex64)
data[:] = np.roll(data, -number)
return result
class MemoryCache(object):
def __init__(self):
self.cacheX = None
self.cacheX_base = None
self.limitsX = None
self.limitsX_base = None
self.cache_used_counter_x = Value('i', 0)
#self.cache_renewed_counter_x = Value('i', 0)
self.image_shape_x = None
self.cache_shape_x = None
self.numE_x = None
self.cacheY = None
self.cacheY_base = None
self.limitsY = None
self.limitsY_base = None
self.cache_used_counter_y = Value('i', 0)
#self.cache_renewed_counter_y = Value('i', 0)
self.image_shape_y = None
self.cache_shape_y = None
self.numE_y = None
self.cache_size = CACHE_SIZE
self.cache_period = CACHE_REUSE_PERIOD
self.renew_cache = Value(ctypes.c_bool, False)
self.cache_used_counter = Value('i', 0)
self.cache_renewed_counter = Value('i', 0)
self._memlock_ = Lock()
def set_image_shape_x(self, image_shape):
self.image_shape_x = image_shape
self.cache_shape_x = (self.cache_size, ) + self.image_shape_x
def set_number_channels_x(self, num_channels):
self.numE_x = num_channels
def set_image_shape_y(self, image_shape):
self.image_shape_y = image_shape
self.cache_shape_y = (self.cache_size, ) + self.image_shape_y
def set_number_channels_y(self, num_channels):
self.numE_y = num_channels
def allocate(self):
nitems_x = 1
nitems_y = 1
for i in range(0, len(self.cache_shape_x)):
nitems_x *= self.cache_shape_x[i]
for i in range(0, len(self.cache_shape_y)):
nitems_y *= self.cache_shape_y[i]
self.cacheX_base = Array(ctypes.c_float, nitems_x)
self.cacheX = numpy.ctypeslib.as_array(self.cacheX_base.get_obj())
self.cacheX = self.cacheX.reshape(self.cache_shape_x)
self.limitsX_base = Array(ctypes.c_double,
self.cache_size * self.numE_x * 2)
self.limitsX = numpy.ctypeslib.as_array(self.limitsX_base.get_obj())
self.limitsX = self.limitsX.reshape((self.cache_size, self.numE_x, 2))
self.cacheY_base = Array(ctypes.c_float, nitems_y)
self.cacheY = numpy.ctypeslib.as_array(self.cacheY_base.get_obj())
self.cacheY = self.cacheY.reshape(self.cache_shape_y)
self.limitsY_base = Array(ctypes.c_double,
self.cache_size * self.numE_y * 2)
self.limitsY = numpy.ctypeslib.as_array(self.limitsY_base.get_obj())
self.limitsY = self.limitsY.reshape((self.cache_size, self.numE_y, 2))
self.renew_cache = Value(ctypes.c_bool, True)
self.cache_used_counter = Value('i', 0)
self.cache_used_counter_x = Value('i', 0)
self.cache_used_counter_y = Value('i', 0)
self.cache_renewed_counter = Value('i', 0)
def is_cache_updated(self):
return (self.renew_cache.value is False)
def get_number_renewed_items(self):
return int(self.cache_renewed_counter.value)
def get_renew_index(self):
#self._memlock_.acquire()
result = 0
with self.cache_renewed_counter.get_lock():
result = self.cache_renewed_counter.value
self.cache_renewed_counter.value += 1
if self.cache_renewed_counter.value >= self.cache_size:
with self.renew_cache.get_lock():
self.renew_cache.value = False
with self.cache_renewed_counter.get_lock():
self.cache_renewed_counter.value = 0
if self.cache_used_counter.value >= self.cache_period:
with self.cache_used_counter.get_lock():
self.cache_used_counter.value = 0
with self.cache_used_counter_x.get_lock():
self.cache_used_counter_x.value = 0
with self.cache_used_counter_y.get_lock():
self.cache_used_counter_y.value = 0
#self._memlock_.release()
return result
def get_cache_size(self):
return self.cache_size
def set_cache_item_x(self, index, item):
#self._memlock_.acquire()
#with self._memlock_:
with self.cacheX_base.get_lock():
self.cacheX[index] = item
#print("Cache X - renewed items: {}; used items: {}". format(self.cache_renewed_counter, self.cache_used_counter_x))
#self._memlock_.release()
def set_item_limits_x(self, index, minval, maxval):
with self.limitsX_base.get_lock():
self.limitsX[index, :, 0] = minval
self.limitsX[index, :, 1] = maxval
def set_cache_item_y(self, index, item):
#self._memlock_.acquire()
#with self._memlock_:
with self.cacheY_base.get_lock():
self.cacheY[index] = item
#self._memlock_.release()
def set_item_limits_y(self, index, minval, maxval):
with self.limitsY_base.get_lock():
self.limitsY[index, :, 0] = minval
self.limitsY[index, :, 1] = maxval
def get_cache_item_x(self, index):
result = None
#self._memlock_.acquire()
#with self._memlock_:
with self.cacheX_base.get_lock():
result = self.cacheX[index]
with self.cache_used_counter_x.get_lock():
self.cache_used_counter_x.value += 1
with self.cache_used_counter.get_lock():
self.cache_used_counter.value = max(
self.cache_used_counter_x.value,
self.cache_used_counter_y.value)
if self.cache_used_counter.value >= self.cache_period:
with self.renew_cache.get_lock():
self.renew_cache.value = True
#print("Cache X - renewed items: {}; used items: {}".format(self.cache_renewed_counter, self.cache_used_counter_x))
#self._memlock_.release()
return result
def get_item_limits_x(self, index):
minval = None
maxval = None
with self.limitsX_base.get_lock():
minval = self.limitsX[index, :, 0]
maxval = self.limitsX[index, :, 1]
return numpy.squeeze(minval), numpy.squeeze(maxval)
def get_cache_item_y(self, index):
result = None
#self._memlock_.acquire()
#with self._memlock_:
with self.cacheY_base.get_lock():
result = self.cacheY[index]
with self.cache_used_counter_y.get_lock():
self.cache_used_counter_y.value += 1
with self.cache_used_counter.get_lock():
self.cache_used_counter.value = max(
self.cache_used_counter_x.value,
self.cache_used_counter_y.value)
if self.cache_used_counter.value >= self.cache_period:
with self.renew_cache.get_lock():
self.renew_cache.value = True
#self._memlock_.release()
return result
def get_item_limits_y(self, index):
minval = None
maxval = None
with self.limitsY_base.get_lock():
minval = self.limitsY[index, :, 0]
maxval = self.limitsY[index, :, 1]
return numpy.squeeze(minval), numpy.squeeze(maxval)
class Screen(Device):
def __init__(self, nomenclature="", width=0., height=0., screen_width=0., screen_height=0.):
Device.__init__(self, nomenclature, width, height)
self.screen_width = screen_width
self.screen_height = screen_height
self.count = Array('i', 10000)
def __repr__(self):
r = str(self) + "("
r += "width=" + str(self.width) + "m, "
r += "height=" + str(self.height) + "m, "
r += "length=" + str(self.length) + "m, "
r += "screen_width=" + str(self.screen_width) + "m, "
r += "screen_height=" + str(self.screen_height) + "m )"
return r
def transport(self, particle):
if not self.is_particle_lost(particle):
self.collect(particle)
if self.next:
return self.next.transport(particle)
else:
return particle
else:
return None
def collect(self, particle):
half_screen_width = 0.5 * self.screen_width
half_screen_height = 0.5 * self.screen_height
cell_width = 0.01 * self.screen_width
cell_height = 0.01 * self.screen_height
if half_screen_width > particle.x > -half_screen_width and half_screen_height > particle.y > -half_screen_height:
x = int((particle.x + half_screen_width) / cell_width)
y = int((particle.y + half_screen_height) / cell_height)
with self.count.get_lock():
self.count[100 * x + y] += 1
def num_of_particles(self):
c = 0
for i in self.count:
c += i
return c
def reset(self):
self.count = Array('i', 10000)
if self.next:
self.next.reset()
def show(self):
x = []
y = []
z = []
for i in range(100):
for j in range(100):
x.append(float(i))
y.append(float(j))
z.append(float(self.count[100 * i + j]))
plt.hist2d(x, y, bins=100, weights=z)
plt.colorbar()
plt.show()
