def test_lumidata():
from numba import types
from numba.typed import Dict
lumidata = LumiData("tests/samples/lumi_small.csv")
runslumis = np.zeros((10, 2), dtype=np.uint32)
runslumis[:, 0] = lumidata._lumidata[0:10, 0]
runslumis[:, 1] = lumidata._lumidata[0:10, 1]
l = lumidata.get_lumi(runslumis)
diff = abs(l - 1.539941814)
print("lumi:", l, "diff:", diff)
assert (diff < 1e-4)
# test build_lumi_table_kernel
py_index = Dict.empty(key_type=types.Tuple([types.uint32, types.uint32]),
value_type=types.float64)
pyruns = lumidata._lumidata[:, 0].astype('u4')
pylumis = lumidata._lumidata[:, 1].astype('u4')
LumiData.build_lumi_table_kernel.py_func(pyruns, pylumis,
lumidata._lumidata, py_index)
assert (len(py_index) == len(lumidata.index))
# test get_lumi_kernel
py_tot_lumi = np.zeros((1, ), dtype=np.float64)
LumiData.get_lumi_kernel.py_func(runslumis[:, 0], runslumis[:, 1],
py_index, py_tot_lumi)
assert (abs(py_tot_lumi[0] - l) < 1e-4)
def test_lumilist():
lumidata = LumiData("tests/samples/lumi_small.csv")
runslumis1 = np.zeros((10, 2), dtype=np.uint32)
runslumis1[:, 0] = lumidata._lumidata[0:10, 0]
runslumis1[:, 1] = lumidata._lumidata[0:10, 1]
runslumis2 = np.zeros((10, 2), dtype=np.uint32)
runslumis2[:, 0] = lumidata._lumidata[10:20, 0]
runslumis2[:, 1] = lumidata._lumidata[10:20, 1]
llist1 = LumiList(runs=runslumis1[:, 0], lumis=runslumis1[:, 1])
llist2 = LumiList(runs=runslumis2[:, 0], lumis=runslumis2[:, 1])
llist3 = LumiList()
llist3 += llist1
llist3 += llist2
lumi1 = lumidata.get_lumi(llist1)
lumi2 = lumidata.get_lumi(llist2)
lumi3 = lumidata.get_lumi(llist3)
assert (abs(lumi3 - (lumi1 + lumi2)) < 1e-4)
llist1.clear()
assert (llist1.array.size == 0)
def test_lumidata():
from numba import types
from numba.typed import Dict
lumidata = LumiData("tests/samples/lumi_small.csv")
# pickle & unpickle
lumidata_pickle = cloudpickle.loads(cloudpickle.dumps(lumidata))
# check same internal lumidata
assert np.all(lumidata._lumidata == lumidata_pickle._lumidata)
runslumis = np.zeros((10, 2), dtype=np.uint32)
results = {"lumi": {}, "index": {}}
for ld in lumidata, lumidata_pickle:
runslumis[:, 0] = ld._lumidata[0:10, 0]
runslumis[:, 1] = ld._lumidata[0:10, 1]
lumi = ld.get_lumi(runslumis)
results["lumi"][ld] = lumi
diff = abs(lumi - 1.539941814)
print("lumi:", lumi, "diff:", diff)
assert diff < 1e-4
# test build_lumi_table_kernel
py_index = Dict.empty(
key_type=types.Tuple([types.uint32, types.uint32]), value_type=types.float64
)
pyruns = ld._lumidata[:, 0].astype("u4")
pylumis = ld._lumidata[:, 1].astype("u4")
LumiData._build_lumi_table_kernel.py_func(
pyruns, pylumis, ld._lumidata, py_index
)
assert len(py_index) == len(ld.index)
# test get_lumi_kernel
py_tot_lumi = np.zeros((1,), dtype=np.float64)
LumiData._get_lumi_kernel.py_func(
runslumis[:, 0], runslumis[:, 1], py_index, py_tot_lumi
)
assert abs(py_tot_lumi[0] - lumi) < 1e-4
# store results:
results["lumi"][ld] = lumi
results["index"][ld] = ld.index
assert np.all(results["lumi"][lumidata] == results["lumi"][lumidata_pickle])
assert len(results["index"][lumidata]) == len(results["index"][lumidata_pickle])
def test_lumimask():
lumimask = LumiMask(
"tests/samples/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON.txt"
)
# pickle & unpickle
lumimask_pickle = cloudpickle.loads(cloudpickle.dumps(lumimask))
# check same mask keys
keys = lumimask._masks.keys()
assert keys == lumimask_pickle._masks.keys()
# check same mask values
assert all(np.all(lumimask._masks[k] == lumimask_pickle._masks[k]) for k in keys)
runs = np.array([303825, 123], dtype=np.uint32)
lumis = np.array([115, 123], dtype=np.uint32)
for lm in lumimask, lumimask_pickle:
mask = lm(runs, lumis)
print("mask:", mask)
assert mask[0]
assert not mask[1]
# test underlying py_func
py_mask = np.zeros(dtype="bool", shape=runs.shape)
LumiMask._apply_run_lumi_mask_kernel.py_func(lm._masks, runs, lumis, py_mask)
assert np.all(mask == py_mask)
assert np.all(lumimask(runs, lumis) == lumimask_pickle(runs, lumis))
def test_lumidata():
lumidata = LumiData("tests/samples/lumi_small.csv")
runslumis = np.zeros((10, 2), dtype=np.uint32)
runslumis[:, 0] = lumidata._lumidata[0:10, 0]
runslumis[:, 1] = lumidata._lumidata[0:10, 1]
l = lumidata.get_lumi(runslumis)
diff = abs(l - 1.539941814)
print("lumi:", l, "diff:", diff)
assert (diff < 0.1)
def test_lumimask():
lumimask = LumiMask(
"tests/samples/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON.txt"
)
runs = np.array([303825, 123], dtype=np.uint32)
lumis = np.array([115, 123], dtype=np.uint32)
mask = lumimask(runs, lumis)
print("mask:", mask)
assert (mask[0] == True)
assert (mask[1] == False)
# test underlying py_func
py_mask = np.zeros(dtype='bool', shape=runs.shape)
LumiMask.apply_run_lumi_mask_kernel.py_func(lumimask._masks, runs, lumis,
py_mask)
assert (np.all(mask == py_mask))
