def setup(self):
"""Perform necessary initialisation."""
self.MasterNode.disable_hv() # In case already setup and LV is enabled
self.MasterNode.initialise_lv()
self.MasterNode.set_hv_bias(120)
# self.MasterNode.enable_hv()
node_threads = []
for node in self.Nodes:
node_threads.append(util.spawn_thread(node.setup))
util.wait_for_threads(node_threads)
def test_spawn_thread(self, thread_init_mock):
thread_mock = MagicMock()
thread_init_mock.return_value = thread_mock
function_mock = MagicMock()
response = util.spawn_thread(function_mock, "arg1", arg2="arg2")
thread_init_mock.assert_called_once_with(target=function_mock,
args=("arg1", ),
kwargs=dict(arg2="arg2"))
thread_mock.start.assert_called_once_with()
self.assertEqual(thread_mock, response)
def unmask_pixels(self, node=None, chips=None):
"""Reset pixelmask for the given chips.
Args:
node(int): Node to unmask - If None, all nodes included
chips(list(int)): List of chips to include in equalisation - If
None, all chips included
"""
nodes, chips = self._validate(node, chips)
node_threads = []
for node in nodes:
node_threads.append(util.spawn_thread(node.unmask_pixels, chips))
util.wait_for_threads(node_threads)
def optimise_gnd_fbk_cas(self, node_id=None, chips=None):
"""Optimise GND, FBK and CAS for the given node and chips.
Args:
node_id(int): Node to optimise - If None, all nodes included
chips(list(int)): List of chips to include in optimisation - If
None, all chips included
"""
nodes, chips = self._validate(node_id, chips)
node_threads = []
for node in nodes:
node_threads.append(
util.spawn_thread(node.optimise_gnd_fbk_cas, chips))
util.wait_for_threads(node_threads)
def acquire_tp_image(self, tp_mask):
"""Load the given test pulse mask and capture a tp image.
Args:
tp_mask(str): Mask file in config directory
"""
node_threads = []
for node in self.Nodes:
node_threads.append(
util.spawn_thread(node.acquire_tp_image, tp_mask))
images = util.wait_for_threads(node_threads)
detector_image = self._combine_images(images)
plot_name = util.tag_plot_name("TPImage", "Detector")
self.dawn.plot_image(detector_image, plot_name)
def full_calibration(self, node_id=None):
"""Perform the full calibration process.
Args:
node_id(int): Node to optimise - If None, all nodes included
"""
nodes, _ = self._validate(node_id)
node_threads = []
for node_ in nodes:
node_threads.append(
util.spawn_thread(self._try_node_full_calibration, node_))
util.wait_for_threads(node_threads)
while self.errors:
error = self.errors.pop()
self.logger.info(error[0], *error[1])
def expose(self, exposure_time):
"""Acquire single image.
Args:
exposure_time(int): Acquire time for image
Returns:
numpy.array: Image data
"""
node_threads = []
for node in self.Nodes:
node_threads.append(util.spawn_thread(node.expose, exposure_time))
images = util.wait_for_threads(node_threads)
detector_image = self._combine_images(images)
plot_name = util.tag_plot_name("Image", "Detector")
self.dawn.plot_image(detector_image, plot_name)
def threshold_equalization(self, node_id=None, chips=None):
"""Calibrate discriminator equalization for given chips in detector.
Args:
node_id(int): Node to equalise - If None, all nodes included
chips(list(int)): List of chips to include in equalisation - If
None, all chips included
"""
nodes, chips = self._validate(node_id, chips)
node_threads = []
for node_ in nodes:
node_threads.append(
util.spawn_thread(self._try_node_threshold_equalization, node_,
chips))
util.wait_for_threads(node_threads)
while self.errors:
error = self.errors.pop()
self.logger.info(error[0], *error[1])
def load_config(self):
"""Load detector configuration files and default thresholds."""
node_threads = []
for node in self.Nodes:
node_threads.append(util.spawn_thread(node.load_config))
util.wait_for_threads(node_threads)