def test_formats(self, capsys, logging_state):
settings.logfile = sys.stderr
settings.verbosity = Verbosity.debug
logg.error("0")
assert capsys.readouterr().err == "ERROR: 0\n"
logg.warning("1")
assert capsys.readouterr().err == "WARNING: 1\n"
logg.info("2")
assert capsys.readouterr().err == "2\n"
logg.hint("3")
assert capsys.readouterr().err == "--> 3\n"
def fit(
self,
x: Optional[np.ndarray] = None,
y: Optional[np.ndarray] = None,
w: Optional[np.ndarray] = None,
**kwargs,
) -> "GAM":
"""
%(base_model_fit.full_desc)s
Parameters
----------
%(base_model_fit.parameters)s
Returns
-------
:class:`cellrank.ul.models.GAM`
Fits the model and returns self.
""" # noqa
super().fit(x, y, w, **kwargs)
if self._grid is not None:
# use default search
grid = {} if not isinstance(self._grid, dict) else self._grid
try:
self.model.gridsearch(
self.x,
self.y,
weights=self.w,
keep_best=True,
progress=False,
**grid,
**kwargs,
)
return self
except Exception as e:
# workaround for: https://github.com/dswah/pyGAM/issues/273
self.model.fit(self.x, self.y, weights=self.w, **kwargs)
logg.error(
f"Grid search failed, reason: `{e}`. Fitting with default values"
)
try:
self.model.fit(self.x, self.y, weights=self.w, **kwargs)
return self
except Exception as e:
raise RuntimeError(
f"Unable to fit `{type(self).__name__}` for gene "
f"`{self._gene!r}` in lineage `{self._lineage!r}`. Reason: `{e}`"
) from e
def test_logfile(self, tmp_path, logging_state):
settings.verbosity = Verbosity.hint
io = StringIO()
settings.logfile = io
assert settings.logfile is io
assert settings.logpath is None
logg.error("test!")
assert io.getvalue() == "ERROR: test!\n"
p = tmp_path / "test.log"
settings.logpath = p
assert settings.logpath == p
assert settings.logfile.name == str(p)
logg.hint("test2")
logg.debug("invisible")
assert settings.logpath.read_text() == "--> test2\n"