def test_full(self):
test_dir = test_subdir_create("assign_test_full")
np.random.seed(123456789)
input_mtl = os.path.join(test_dir, "mtl.fits")
input_std = os.path.join(test_dir, "standards.fits")
input_sky = os.path.join(test_dir, "sky.fits")
input_suppsky = os.path.join(test_dir, "suppsky.fits")
tgoff = 0
nscience = sim_targets(input_mtl,
TARGET_TYPE_SCIENCE,
tgoff,
density=self.density_science)
tgoff += nscience
nstd = sim_targets(input_std,
TARGET_TYPE_STANDARD,
tgoff,
density=self.density_standards)
tgoff += nstd
nsky = sim_targets(input_sky,
TARGET_TYPE_SKY,
tgoff,
density=self.density_sky)
tgoff += nsky
nsuppsky = sim_targets(input_suppsky,
TARGET_TYPE_SUPPSKY,
tgoff,
density=self.density_suppsky)
tgs = Targets()
load_target_file(tgs, input_mtl)
load_target_file(tgs, input_std)
load_target_file(tgs, input_sky)
load_target_file(tgs, input_suppsky)
# Create a hierarchical triangle mesh lookup of the targets positions
tree = TargetTree(tgs, 0.01)
# Read hardware properties
fp, exclude, state = sim_focalplane(rundate=test_assign_date)
hw = load_hardware(focalplane=(fp, exclude, state))
tfile = os.path.join(test_dir, "footprint.fits")
sim_tiles(tfile)
tiles = load_tiles(tiles_file=tfile)
# Compute the targets available to each fiber for each tile.
tgsavail = TargetsAvailable(hw, tgs, tiles, tree)
# Free the tree
del tree
# Compute the fibers on all tiles available for each target
favail = LocationsAvailable(tgsavail)
# Create assignment object
asgn = Assignment(tgs, tgsavail, favail)
# First-pass assignment of science targets
asgn.assign_unused(TARGET_TYPE_SCIENCE)
# Redistribute science targets
asgn.redistribute_science()
# Assign standards, 10 per petal
asgn.assign_unused(TARGET_TYPE_STANDARD, 10)
asgn.assign_force(TARGET_TYPE_STANDARD, 10)
# Assign sky to unused fibers, up to 40 per petal
asgn.assign_unused(TARGET_TYPE_SKY, 40)
asgn.assign_force(TARGET_TYPE_SKY, 40)
# Use supplemental sky to meet our requirements
asgn.assign_unused(TARGET_TYPE_SUPPSKY, 40)
asgn.assign_force(TARGET_TYPE_SUPPSKY, 40)
# If there are any unassigned fibers, try to place them somewhere.
asgn.assign_unused(TARGET_TYPE_SCIENCE)
asgn.assign_unused(TARGET_TYPE_SKY)
asgn.assign_unused(TARGET_TYPE_SUPPSKY)
write_assignment_fits(tiles, asgn, out_dir=test_dir, all_targets=True)
plotpetals = [0]
#plotpetals = None
plot_tiles(hw,
tiles,
result_dir=test_dir,
plot_dir=test_dir,
result_prefix="fba-",
real_shapes=True,
petals=plotpetals,
serial=True)
qa_tiles(hw, tiles, result_dir=test_dir)
qadata = None
with open(os.path.join(test_dir, "qa.json"), "r") as f:
qadata = json.load(f)
for tile, props in qadata.items():
self.assertTrue(props["assign_science"] >= 4485)
self.assertEqual(100, props["assign_std"])
self.assertTrue(
(props["assign_sky"] + props["assign_suppsky"]) >= 400)
plot_qa(qadata,
os.path.join(test_dir, "qa"),
outformat="pdf",
labels=True)
return
def test_full(self):
test_dir = test_subdir_create("assign_test_full")
np.random.seed(123456789)
input_mtl = os.path.join(test_dir, "mtl.fits")
input_std = os.path.join(test_dir, "standards.fits")
input_sky = os.path.join(test_dir, "sky.fits")
nscience = sim_targets(input_mtl, TARGET_TYPE_SCIENCE, 0)
nstd = sim_targets(input_std, TARGET_TYPE_STANDARD, nscience)
nsky = sim_targets(input_sky, TARGET_TYPE_SKY, (nscience + nstd))
tgs = Targets()
load_target_file(tgs, input_mtl)
load_target_file(tgs, input_std)
load_target_file(tgs, input_sky)
# Create a hierarchical triangle mesh lookup of the targets positions
tree = TargetTree(tgs, 0.01)
# Read hardware properties
fstatus = os.path.join(test_dir, "fiberstatus.ecsv")
sim_status(fstatus)
hw = load_hardware(status_file=fstatus)
tfile = os.path.join(test_dir, "footprint.fits")
sim_tiles(tfile)
tiles = load_tiles(tiles_file=tfile)
# Compute the targets available to each fiber for each tile.
tgsavail = TargetsAvailable(hw, tgs, tiles, tree)
# Free the tree
del tree
# Compute the fibers on all tiles available for each target
favail = FibersAvailable(tgsavail)
# Create assignment object
asgn = Assignment(tgs, tgsavail, favail)
# First-pass assignment of science targets
asgn.assign_unused(TARGET_TYPE_SCIENCE)
# Redistribute science targets
asgn.redistribute_science()
# Assign standards, 10 per petal
asgn.assign_unused(TARGET_TYPE_STANDARD, 10)
asgn.assign_force(TARGET_TYPE_STANDARD, 10)
# Assign sky to unused fibers, up to 40 per petal
asgn.assign_unused(TARGET_TYPE_SKY, 40)
asgn.assign_force(TARGET_TYPE_SKY, 40)
# If there are any unassigned fibers, try to place them somewhere.
asgn.assign_unused(TARGET_TYPE_SCIENCE)
asgn.assign_unused(TARGET_TYPE_SKY)
write_assignment_fits(tiles, asgn, out_dir=test_dir, all_targets=True)
plot_tiles(hw,
tiles,
result_dir=test_dir,
plot_dir=test_dir,
petals=[0],
serial=True)
qa_tiles(hw, tiles, result_dir=test_dir)
qadata = None
with open(os.path.join(test_dir, "qa.json"), "r") as f:
qadata = json.load(f)
for tile, props in qadata.items():
self.assertEqual(4495, props["assign_science"])
self.assertEqual(100, props["assign_std"])
self.assertEqual(400, props["assign_sky"])
plot_qa(qadata,
os.path.join(test_dir, "qa"),
outformat="pdf",
labels=True)
return
# -------------------------------------------------------------------------------------------------- # FIBER ASSIGNMENT PROCESS # # Fiber assignment process is carried out here. Results are stored in the Assignment type object. # -------------------------------------------------------------------------------------------------- # First-pass assignment of science targets asgn.assign_unused(TARGET_TYPE_SCIENCE) # Redistribute science targets across available petals asgn.redistribute_science() # Assign standards, 10 per petal asgn.assign_unused(TARGET_TYPE_STANDARD, 10) asgn.assign_force(TARGET_TYPE_STANDARD, 10) # Assign sky, up to 40 per petal asgn.assign_unused(TARGET_TYPE_SKY, 40) asgn.assign_force(TARGET_TYPE_SKY, 40) # If there are any unassigned fibers, try to place them somewhere. asgn.assign_unused(TARGET_TYPE_SCIENCE) asgn.assign_unused(TARGET_TYPE_SKY) # -------------------------------------------------------------------------------------------------- # EXTRACTING THE ASSIGNED TARGET IDS # # In this part the assigned target IDs are extracted from the relevant objects. Each realization is # saved in .npy format. # --------------------------------------------------------------------------------------------------