def test__get_dblock_paths__required_group_not_present():
with TMPDir() as tmpdir:
TEST_FILE = tmpdir + "file.h5"
TEST_GROUP = "group"
# create empty file, no groups
h5py.File(TEST_FILE, "w").close()
with pytest.raises(ValueError) as group_does_not_exist_err:
h5tools.get_dblock_paths(TEST_FILE, TEST_GROUP)
assert "does not exist" in str(group_does_not_exist_err.value)
def test__get_dblock_paths__no_dblocks():
with TMPDir() as tmpdir:
TEST_FILE = tmpdir + "file.h5"
TEST_GROUP = "group"
# create required data group, but no dblocks
with h5py.File(TEST_FILE, "w") as tf:
tf.create_group(TEST_GROUP)
with pytest.raises(ValueError) as no_dblocks_err:
h5tools.get_dblock_paths(TEST_FILE, TEST_GROUP)
assert "No dblocks found" in str(no_dblocks_err.value)
def test__get_dblock_paths__disordered_dblocks():
with TMPDir() as tmpdir:
TEST_FILE = tmpdir + "file.h5"
TEST_GROUP = "group"
with h5py.File(TEST_FILE, "w") as tf:
grp = tf.create_group(TEST_GROUP)
for i in range(3):
grp.create_dataset(f"dblock_{i}", data=())
grp.create_dataset("dblock_4", data=())
# now have dblock_0, dblock_1, dblock_2, dblock_4
# dblock_3 missing
with pytest.raises(ValueError) as disordered_dblocks_err:
h5tools.get_dblock_paths(TEST_FILE, TEST_GROUP)
assert "Disordered dblocks" in str(disordered_dblocks_err.value)
def test__get_dblock_paths__as_expected():
with TMPDir() as tmpdir:
TEST_FILE = tmpdir + "file.h5"
TEST_GROUP = "group"
with h5py.File(TEST_FILE, "w") as tf:
grp = tf.create_group(TEST_GROUP)
grp.create_dataset(f"dblock_1", data=())
grp.create_dataset(f"dblock_0", data=())
grp.create_dataset(f"dblock_2", data=())
expected = ["group/dblock_0", "group/dblock_1", "group/dblock_2"]
actual = h5tools.get_dblock_paths(TEST_FILE, TEST_GROUP)
assert expected == actual
def test_irb_calibrate_logpoked_cals():
"""test that calibration ignores logpoked cals"""
pfx = "arquant2"
h5f = IRB_DIR / "mkh5" / "logpoked_cals_test.h5"
mydat = mkh5.mkh5(h5f)
mydat.reset_all() # a = read/write, create if needed
mydat.create_mkdata(pfx, *GET_IRB_MKDIG(pfx))
mydat.calibrate_mkdata(
pfx,
n_points=3, # pts to average, either side of cursor
cal_size=10, # uV
polarity=1, # of calibration pulse
lo_cursor=-50, # ms
hi_cursor=50,
cal_ccode=0,
use_cals=None,
)
hio = mydat.HeaderIO()
dblock_paths = h5tools.get_dblock_paths(h5f, pfx)
lo_gain_chans = ["lle", "lhz", "rle", "rhz", "MiPf", "LLPf", "RLPf"]
with h5py.File(h5f, "r+") as h5:
for dbp in dblock_paths:
dblock = h5[dbp]
hio.get(dblock)
streams = hio.header["streams"]
for k, stream in streams.items():
if "dig_chan_" in stream["source"]:
scale_by = None
scale_by = abs(stream["cals"]["scale_by"])
if stream["name"] in lo_gain_chans:
assert 17.0 < scale_by and scale_by < 22.0
else:
assert 34.0 < scale_by and scale_by < 44.0