def test_fixed_point_column_transform(tmp_path):
""" ensure a user-added column transform is applied """
from ctapipe.io.tableio import FixedPointColumnTransform
tmp_file = tmp_path / "test_column_transforms.hdf5"
class SomeContainer(Container):
container_prefix = ""
image = Field(np.array([np.nan, np.inf, -np.inf]))
cont = SomeContainer()
with HDF5TableWriter(tmp_file, group_name="data") as writer:
writer.add_column_transform(
"signed", "image",
FixedPointColumnTransform(100, 0, np.float64, np.int32))
writer.add_column_transform(
"unsigned",
"image",
FixedPointColumnTransform(100, 0, np.float64, np.uint32),
)
# add user generated transform for the "value" column
writer.write("signed", cont)
writer.write("unsigned", cont)
with HDF5TableReader(tmp_file, mode="r") as reader:
signed = next(reader.read("/data/signed", SomeContainer()))
unsigned = next(reader.read("/data/unsigned", SomeContainer()))
for data in (signed, unsigned):
# check we get our original nans back
assert np.isnan(data.image[0])
assert np.isposinf(data.image[1])
assert np.isneginf(data.image[2])
def test_column_transforms(tmp_path):
""" ensure a user-added column transform is applied """
from ctapipe.containers import NAN_TIME
from ctapipe.io.tableio import FixedPointColumnTransform
tmp_file = tmp_path / "test_column_transforms.hdf5"
class SomeContainer(Container):
container_prefix = ""
current = Field(1 * u.A, unit=u.uA)
time = Field(NAN_TIME)
image = Field(np.array([1.234, 123.456]))
cont = SomeContainer()
with HDF5TableWriter(tmp_file, group_name="data") as writer:
writer.add_column_transform(
"mytable", "image",
FixedPointColumnTransform(100, 0, np.float64, np.int32))
# add user generated transform for the "value" column
writer.write("mytable", cont)
# check that we get a length-3 array when reading back
with HDF5TableReader(tmp_file, mode="r") as reader:
data = next(reader.read("/data/mytable", SomeContainer()))
assert data.current.value == 1e6
assert data.current.unit == u.uA
assert isinstance(data.time, Time)
assert data.time == NAN_TIME
# rounded to two digits
assert np.all(data.image == np.array([1.23, 123.45]))