def test_returns_dict_keyword_renames():
res = {"1": 1, "2": 2}
op = operation(lambda: res, provides=keyword("11", "1"), returns_dict=True)
assert op.compute({}) == {"11": 1}
assert len(res) == 2 # check it did not mutate results
res = {"1": 1, "11": 11}
op = operation(lambda: res, provides=keyword("11", "1"), returns_dict=True)
assert op.compute({}) == {"11": 1} # original '11' was discarded
assert len(res) == 2 # check it did not mutate results
def test_keyword_jsonp():
op = operation(lambda *, bar: bar * 2,
"kw",
needs=keyword("foo/bar"),
provides="a")
sol = op.compute({"foo/bar": "ciao"})
assert sol == {"a": "ciaociao"}
def param_to_modifier(name: str, param: inspect.Parameter) -> str:
return (
optional(name)
# is optional?
if param.default is not inspect._empty # type: ignore
else keyword(name)
if param.kind == Parameter.KEYWORD_ONLY
else name
)
def test_cwd_fnop():
op = operation(
str,
None,
needs=[
"a",
"a/b",
"/r/b",
optional("o"),
keyword("k"),
implicit("i"),
vararg("v1"),
varargs("v2"),
sfx("s1"),
sfxed("s2", "s22"),
vcat("vc"),
],
provides=["A/B", "C", "/R"],
aliases=[("A/B", "aa"), ("C", "CC"), ("/R", "RR")],
cwd="root",
)
exp = """
FnOp(name='str',
needs=['root/a'($),
'root/a/b'($),
'/r/b'($),
'root/o'($?'o'),
'root/k'($>'k'),
'root/i'($),
'root/v1'($*),
'root/v2'($+),
sfx('s1'),
sfxed('root/s2'($),
's22'),
'root/vc'($)],
provides=['root/A/B'($),
'root/C'($),
'/R'($),
'root/aa'($),
'root/CC'($),
'root/RR'($)],
aliases=[('root/A/B'($), 'root/aa'($)),
('root/C'($), 'root/CC'($)),
('/R'($), 'root/RR'($))],
fn='str')
"""
assert oneliner(op) == oneliner(exp)
def test_conveyor_identity_fn():
op = operation(name="copy values", needs="a")()
assert not op.fn
op = operation(None, needs="a", provides="A")
assert not op.fn
op = operation(None, name="a", needs="a", provides="A")
assert op.fn
assert op(a=5) == {"A": 5}
op = operation(name="a", needs=["a", "b"], provides=["A", "B"])()
assert op.compute({"a": 5, "b": 6}) == {"A": 5, "B": 6}
op = operation(name="a", needs=["a", keyword("b")], provides=["A", "B"])()
assert op(a=55, b=66) == {"A": 55, "B": 66}
op = operation(
fn=None,
name="a",
needs=[optional("a"), vararg("b"), "c"],
# positional, vararg, keyword, optional
provides=["C", "B", "A"],
)
assert op(c=7, a=5, b=6) == {"A": 5, "B": 6, "C": 7}
"n_min_drive2_stopdecel",
"n_min_drive2",
"n_min_drive_set",
"n_min_drive_up",
"n_min_drive_up_start",
"n_min_drive_down",
"n_min_drive_down_start",
"t_cold_end",
),
)
#: Consume (R)ounded values to construct a :class:`_NMinDrives` instance.
NMinDrives = autographed(
_NMinDrives,
needs=[
keyword(n if n == "t_cold_end" else f"{n}_R", n)
for n in _NMinDrives._fields
],
inp_sideffects="valid: n_min_drives",
provides="n_min_drives",
)
def _compose_mdl_2_n_min_drives(aug: autog.Autograph = None,
**pipeline_kw) -> "Pipeline": # type: ignore
aug = Autograph(["calc_", "upd_"])
funcs = FnHarvester(base_modules=[__name__]).harvest()
ops = aug.wrap_funcs(funcs)
return compose("mdl_2_n_min_drives", *ops, **pipeline_kw)
roots_head[0],
v_max,
wot.loc[v_max - 5 * v_step : v_max + 5 * v_step, w.p_remain_stable],
)
rec = VMaxRec(v_max, n_v_max, gid, False, wot)
else:
rec = VMaxRec(np.NAN, np.NAN, gid, False, wot)
return rec
@autog.autographed(
needs=(),
provides=[
*VMaxRec._fields[:-2],
keyword("is_n_lim_vmax", "is_n_lim"),
keyword("vmax_wots", "wot"), # `wot` causes cycle!
],
inp_sideffects=[("gwots", "p_resist"), ("gwots", "p_avail")],
returns_dict=True,
)
def calc_v_max(gwots: Union[pd.Series, pd.DataFrame]) -> VMaxRec:
"""
Finds maximum velocity by scanning gears from the top.
TODO: accept `n_lim`
:param gwots:
a dataframe indexed by a grid of rounded velocities,
containing (at least) `p_resist` and `p_avail_stable` columns for all gears,
as generated by :func:`~.engine.interpolate_wot_on_v_grid()`, and
else:
raise AssertionError("Missing `n_min` ok-flags from:", gflags)
n_ok = inv.AND_columns_with_NANFLAGs(pd.concat(flags_to_AND, axis=1))
assert isinstance(n_ok, pd.Series), ("groupby won't work otherwise", n_ok)
g = flagcols[0][1]
n_ok.name = g
return n_ok
@autog.autographed(
needs=[
# .. AND ...
keyword("cycle/ok_min_n_g3plus_ups"),
keyword("cycle/ok_min_n_g3plus_dns"),
# .. AND ...
keyword("cycle/ok_min_n_g2"),
keyword("cycle/ok_min_n_g2_stopdecel"),
# .. AND ...
keyword("cycle/ok_min_n_g1"),
keyword("cycle/ok_min_n_g1_initaccel"),
# .. ALONE ...
keyword("cycle/OK_max_n"),
],
provides=hcat("cycle/OK_n"),
)
def derrive_ok_n_flags(**ok_n_flags: Mapping[str, pd.DataFrame]):
"""
Merge together all N-allowed flags using AND+OR boolean logic.
