def test_profile_getter_1_7_8():
"""Load a profile from version 1.7.8"""
tdir = pathlib.Path(tempfile.mkdtemp(prefix="cli_profile_"))
name = "cli-profile-1.7.8.cfg"
cfgpath = tdir / name
shutil.copy2(data_path / name, cfgpath)
pf = profile.Profile(path=cfgpath)
assert pf["segment"] == 0
assert pf["segment"] == 0
def test_fit_data():
# use temporary file
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_cli_rate_")
name = pathlib.Path(name)
profile.Profile(path=name)
# this will fit with the profile default parameters
idnt = rating.fit_data(path=jpkfile, profile_path=name)
assert idnt.path == jpkfile
assert idnt.fit_properties["success"]
def test_single_fitparam():
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_profile_")
name = pathlib.Path(name)
pf = profile.Profile(path=name)
# sanity checks (run twice to trigger loading and saving)
pf["fit param E value"] = 50
pf["fit param R value"] = 16e-6
params = pf.get_fit_params()
assert params["E"].value == 50
assert params["R"].value == 16e-6
def test_profile_getter_2_1_0():
"""Load a profile from version 2.1.0"""
tdir = pathlib.Path(tempfile.mkdtemp(prefix="cli_profile_"))
name = "cli-profile-2.1.0.cfg"
cfgpath = tdir / name
shutil.copy2(data_path / name, cfgpath)
pf = profile.Profile(path=cfgpath)
assert pf["segment"] == 0
assert pf["segment"] == 0
assert pf["rating training set"] == "zef18"
def test_profile_fitparams():
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_profile_")
name = pathlib.Path(name)
pf = profile.Profile(path=name)
# sanity checks (run twice to trigger loading and saving)
pf["model_key"] = "hertz_cone"
params = pf.get_fit_params()
params2 = pf.get_fit_params()
assert params == params2
assert len(params) == 5
assert "E" in params.keys()
def test_fit_data_with_user_training_set():
tdir = setup_training_set()
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_cli_rate_")
name = pathlib.Path(name)
pf = profile.Profile(path=name)
pf["rating training set"] = tdir
pf["fit param R value"] = 37.28e-6 / 2
pout = tempfile.mkdtemp(prefix="test_nanite_cli_rate_ts")
pout = pathlib.Path(pout)
rating.fit_perform(path=jpkfile2, path_results=pout, profile_path=name)
stats = np.loadtxt(pout / "statistics.tsv", skiprows=1, usecols=(1, 2, 3))
assert np.all(stats[:, 0] == [109, 129, 416])
assert np.all((3.5 < stats[:, 2]) * (stats[:, 2] < 5))
def test_fit_data_with_zef18():
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_cli_rate_")
name = pathlib.Path(name)
pf = profile.Profile(path=name)
pf["rating training set"] = "zef18"
pf["weight_cp"] = 2e-6
pf["fit param R value"] = 137.28e-6 / 2
pout = tempfile.mkdtemp(prefix="test_nanite_cli_rate_ts")
pout = pathlib.Path(pout)
rating.fit_perform(path=jpkfile2, path_results=pout, profile_path=name)
stats = np.loadtxt(pout / "statistics.tsv", skiprows=1, usecols=(1, 2, 3))
assert np.all(stats[:, 0] == [109, 129, 416])
assert stats[0, 2] == 9.5
assert stats[1, 2] == 2.4
assert stats[2, 2] == 4.9
def test_profile_getter():
_, name = tempfile.mkstemp(suffix=".cfg", prefix="test_nanite_profile_")
name = pathlib.Path(name)
pf = profile.Profile(path=name)
# sanity checks (run twice to trigger loading and saving)
assert pf["segment"] == 0
assert pf["segment"] == 0
assert pf["preprocessing"] == [
"compute_tip_position", "correct_force_offset", "correct_tip_offset"
]
assert pf["preprocessing"] == [
"compute_tip_position", "correct_force_offset", "correct_tip_offset"
]
pf["preprocessing"] = ["compute_tip_position"]
assert pf["preprocessing"] == ["compute_tip_position"]
assert pf["range_x"] == [0, 0]
assert pf["range_x"] == [0, 0]
assert pf["weight_cp"] == 5e-7
assert pf["weight_cp"] == 5e-7