import numpy as np
from ..common import calcSpherical
from concurrent.futures import ThreadPoolExecutor
class ClusterCoordinates:
"""
This class takes care of cluster coordinates
"""
def __init__(self) -> None:
# these are the sensor IDs of the pxd modules/panels from the root file, they are
# use to identify on which panels a cluster event happened
self.panelIDs = np.array([ 8480, 8512, 8736, 8768, 8992, 9024, 9248, 9280,
9504, 9536, 9760, 9792, 10016, 10048, 10272, 10304,
16672, 16704, 16928, 16960, 17184, 17216, 17440, 17472,
17696, 17728, 17952, 17984, 18208, 18240, 18464, 18496,
18720, 18752, 18976, 19008, 19232, 19264, 19488, 19520])
# every line in this corresponds to one entry in the array above, this is used
# to put the projected uv plane in the right position
self.panelShifts = np.array([[ 1.3985 , 0.2652658 , 3.68255],
[ 1.3985 , 0.23238491, -0.88255],
[ 0.80146531, 1.17631236, 3.68255],
[ 0.82407264, 1.15370502, -0.88255],
[-0.2582769 , 1.3985 , 3.68255],
[-0.2322286 , 1.3985 , -0.88255],
[-1.17531186, 0.80246583, 3.68255],
[-1.15510614, 0.82267151, -0.88255],
[-1.3985 , -0.2645974 , 3.68255],
[-1.3985 , -0.23012119, -0.88255],
[-0.80591227, -1.17186534, 3.68255],
[-0.82344228, -1.15433536, -0.88255],
[ 0.26975836, -1.3985 , 3.68255],
[ 0.23326624, -1.3985 , -0.88255],
[ 1.1746111 , -0.80316652, 3.68255],
[ 1.15205703, -0.82572062, -0.88255],
[ 2.2015 , 0.26959865, 5.01305],
[ 2.2015 , 0.2524582 , -1.21305],
[ 1.77559093, 1.32758398, 5.01305],
[ 1.78212569, 1.31626522, -1.21305],
[ 0.87798948, 2.03516717, 5.01305],
[ 0.88478563, 2.03124357, -1.21305],
[-0.26129975, 2.2015 , 5.01305],
[-0.25184137, 2.2015 , -1.21305],
[-1.32416655, 1.77756402, 5.01305],
[-1.31417539, 1.78333226, -1.21305],
[-2.03421133, 0.87964512, 5.01305],
[-2.02960691, 0.88762038, -1.21305],
[-2.2015 , -0.25954151, 5.01305],
[-2.2015 , -0.24969109, -1.21305],
[-1.77636043, -1.32625112, 5.01305],
[-1.78138268, -1.31755219, -1.21305],
[-0.87493138, -2.03693277, 5.01305],
[-0.8912978 , -2.02748378, -1.21305],
[ 0.26489725, -2.2015 , 5.01305],
[ 0.25364439, -2.2015 , -1.21305],
[ 1.3269198 , -1.7759744 , 5.01305],
[ 1.32258793, -1.77847528, -1.21305],
[ 2.03616649, -0.87625871, 5.01305],
[ 2.02936825, -0.8880338 , -1.21305]])
# every entry here corresponds to the entries in the array above, these are
# used for rotating the projected uv plane
self.panelRotations = np.array([ 90, 90, 135, 135, 180, 180, 225, 225, 270, 270, 315, 315, 360,
360, 405, 405, 90, 90, 120, 120, 150, 150, 180, 180, 210, 210,
240, 240, 270, 270, 300, 300, 330, 330, 360, 360, 390, 390, 420,
420])
# the layer and ladder arrays, for finding them from sensor id
self.panelLayer = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])
self.panelLadder = np.array([1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 12, 12, 13, 13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 20, 20, 21, 21])
# all transpormaations are stored in a dict, with the sensor id as a keyword
self.transformation = {}
self.layersLadders = {}
for i in range(len(self.panelIDs)):
self.transformation[self.panelIDs[i]] = [self.panelShifts[i], self.panelRotations[i]]
self.layersLadders[self.panelIDs[i]] = [self.panelLayer[i], self.panelLadder[i]]
def get(self, uPositions: np.ndarray, vPositions: np.ndarray, sensorIDs: np.ndarray) -> dict:
"""
converting the uv coordinates, together with sensor ids, into xyz coordinates
"""
#setting up index chunks for multi threading
indexChunks = np.array_split(range(len(sensorIDs)), 4)
# Initialize result lists
xResults, yResults, zResults = [], [], []
coordinates = {}
with ThreadPoolExecutor(max_workers=4) as executor:
futures = [executor.submit(self._process, uPositions[chunk], vPositions[chunk], sensorIDs[chunk]) for chunk in indexChunks]
for future in futures:
x, y, z = future.result()
xResults.append(x)
yResults.append(y)
zResults.append(z)
coordinates['xPosition'] = np.concatenate(xResults)
coordinates['yPosition'] = np.concatenate(yResults)
coordinates['zPosition'] = np.concatenate(zResults)
return coordinates
def _process(self, uPositions: np.ndarray, vPositions: np.ndarray, sensorIDs: np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""
a private method for transposing/converting 2d uv coords into 3d xyz coordinates
"""
length = len(sensorIDs)
xArr, yArr, zArr = np.zeros(length), np.zeros(length), np.zeros(length)
# iterting over the cluster arrays
for index, (u, v, sensorID) in enumerate(zip(uPositions, vPositions, sensorIDs)):
# grabbing the shift vector and rotation angle
shift, angle = self.transformation[sensorID]
# setting up rotation matrix
theta = np.deg2rad(angle)
rotMatrix = np.array([[np.cos(theta), -np.sin(theta), 0], [np.sin(theta), np.cos(theta), 0], [0, 0, 1]])
# projecting uv coordinates into 3d space
point = np.array([u, 0, v])
# shifting and rotating the projected vector
shifted = rotMatrix.dot(point) + shift
xArr[index], yArr[index], zArr[index] = shifted
return xArr, yArr, zArr
def layers(self, sensorIDs: np.ndarray) -> dict:
"""
looks up the corresponding layers and ladders for every cluster
"""
layersLadders = {}
length = len(sensorIDs)
layers = np.empty(length, dtype=int)
ladders = np.empty(length, dtype=int)
for i, id in enumerate(sensorIDs):
layers[i], ladders[i] = self.layersLadders[id]
return {'layer': np.array(layers, dtype=int),
'ladder': np.array(ladders, dtype=int)}
def sphericals(self, xPosition: np.ndarray, yPosition: np.ndarray, zPosition: np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""
this calculates spherical coordinates from xyz coordinates
"""
return calcSpherical(xPosition, yPosition, zPosition)