def test_generateRandomTargets_method(self, bench):
# Generate the targets
density = 5
targets = targetUtils.generateRandomTargets(density, bench)
# Check that the targets fall within the bench
distances = np.abs(targets.positions - bench.center)
assert np.all(distances <= bench.radius)
# Check that we get the expected density at different test radii
testRadii = bench.radius * np.linspace(0.2, 1, 9)
testTargets = np.sum(distances < testRadii[:, np.newaxis], axis=1)
testDensities = testTargets * (np.mean(bench.cobras.rMax**2) /
testRadii**2)
assert np.all(np.abs(testDensities - density) < 0.2 * density)
def test_calculateAccessibleTargets_method(self, bench, testParameters):
# Extract the test parameters
randomTargetDistribution, targetDensity, useKDTree = testParameters
# Create the targets
if randomTargetDistribution:
targets = targetUtils.generateRandomTargets(targetDensity, bench)
else:
targets = targetUtils.generateOneTargetPerCobra(bench)
# Create a dummy TargetSelector
selector = TargetSelectorSubclass(bench, targets)
# Construct the KD tree if requested
if useKDTree:
selector.constructKDTree()
# Calculate the accessible targets for each cobra
selector.calculateAccessibleTargets()
# Check that the targets fall inside the cobras patrol areas
cobraCenters = bench.cobras.centers
indices = selector.accessibleTargetIndices
positions = targets.positions[indices]
distances = np.abs(cobraCenters[:, np.newaxis] - positions)
validTargets = indices != NULL_TARGET_INDEX
assert np.all(
(distances < bench.cobras.rMax[:, np.newaxis])[validTargets])
assert np.all(
(distances > bench.cobras.rMin[:, np.newaxis])[validTargets])
# Check that the accessible targets are ordered by distance
for i in range(bench.cobras.nCobras):
indices = selector.accessibleTargetIndices[i]
distances = selector.accessibleTargetDistances[i]
validTargets = indices != NULL_TARGET_INDEX
nTargets = np.sum(validTargets)
assert np.all(
distances[:nTargets] == np.sort(distances[validTargets]))
calibrationProduct.L2[~tooLongLinkLengths])
print("Cobras with too long link lenghts: %i" % np.sum(tooLongLinkLengths))
# Load the black dots calibration file
calibrationFileName = os.path.join(
os.environ["PFS_INSTDATA_DIR"],"data/pfi/dot", "black_dots_mm.csv")
blackDotsCalibrationProduct = BlackDotsCalibrationProduct(calibrationFileName)
# Create the bench instance
bench = Bench(layout="calibration", calibrationProduct=calibrationProduct,
blackDotsCalibrationProduct=blackDotsCalibrationProduct)
print("Number of cobras:", bench.cobras.nCobras)
# Generate the targets
targetDensity = 1.5
targets = targetUtils.generateRandomTargets(targetDensity, bench)
print("Number of simulated targets:", targets.nTargets)
# Select the targets
selector = DistanceTargetSelector(bench, targets)
selector.run()
selectedTargets = selector.getSelectedTargets()
# Simulate an observation
start = time.time()
simulator = CollisionSimulator2(bench, cobraCoach, selectedTargets)
simulator.run()
print("Number of cobras involved in collisions:", simulator.nCollisions)
print("Number of cobras unaffected by end collisions: ",
simulator.nCollisions - simulator.nEndPointCollisions)
print("Total simulation time (s):", time.time() - start)
endCollisionsArray = np.zeros(len(maxDistanceArray))
# Load the cobras calibration product
calibrationProduct = CobrasCalibrationProduct(
"updatedMotorMapsFromThisRun2.xml")
# Calculate the collisions for each maxDist-density combination
for i in range(len(maxDistanceArray)):
print("TargetDensity", targetDensityArray[i], "MaxDistance",
maxDistanceArray[i])
# Create the bench instance
bench = Bench(layout="full", calibrationProduct=calibrationProduct)
# Create a random sample of targets
targets = targetUtils.generateRandomTargets(targetDensityArray[i], bench)
# Select the targets
selector = DistanceTargetSelector(bench, targets)
selector.run(maximumDistance=maxDistanceArray[i],
solveCollisions=solveCollisions)
selectedTargets = selector.getSelectedTargets()
# Simulate an observation
simulator = CollisionSimulator(bench, selectedTargets)
simulator.run()
# Fill the statistics arrays
unassignedCobrasArray[i] = np.sum(simulator.assignedCobras == False)
collisionsArray[i] = simulator.nCollisions
endCollisionsArray[i] = simulator.nEndPointCollisions
def targets(bench):
return targetUtils.generateRandomTargets(2, bench)
