def best_match(func, argtypes, constraints=None):
"""
Find a best match in for overloaded function `func` given `argtypes`.
Parameters
----------
func: Dispatcher
Overloaded Blaze function
argtypes: [Mono]
List of input argument types
constraints: [(TypeVar, Mono)]
Optional set of constraints, see unification.py
Returns
-------
Overloaded function as an `Overload` instance.
"""
from blaze.datashape import coercion_cost
overloads = func.overloads
# -------------------------------------------------
# Find candidates
candidates = find_matches(overloads, argtypes, constraints or [])
# -------------------------------------------------
# Weigh candidates
matches = defaultdict(list)
for match in candidates:
in_signature = T.Function(*argtypes + [T.TypeVar('R')])
signature = match.sig
try:
weight = coercion_cost(in_signature, signature)
except error.CoercionError:
pass
else:
matches[weight].append(match)
if not matches:
raise error.OverloadError(
"No overload for function %s matches for argtypes (%s)" % (
func, ", ".join(map(str, argtypes))))
# -------------------------------------------------
# Return candidate with minimum weight
candidates = matches[min(matches)]
if len(candidates) > 1:
raise error.OverloadError(
"Ambiguous overload for function %s with inputs (%s): \n%s" % (
func, ", ".join(map(str, argtypes)),
"\n".join(" %s" % (overload.resolved_sig,) for overload in candidates)))
else:
return candidates[0]
def test_coercion(self):
self.assertEqual(coercion_cost(t1, t2), 0)
self.assertGreater(coercion_cost(t3, t2), 0)
self.assertEqual(coercion_cost(rt1, rt2), 0)
def test_coercion(self):
self.assertGreater(coercion_cost(t3, t2), 0)
def test_coerce_src_ellipsis(self):
a, b, c = dshapes('10, ..., float32', 'X, Y, float64', 'X, ..., float64')
self.assertGreater(coercion_cost(a, b), coercion_cost(a, c))
def test_coerce_traits(self):
a, b, c = dshapes('10, 10, float32', '10, X, A : floating', '10, X, float32')
self.assertGreater(coercion_cost(a, b), coercion_cost(a, c))
def test_coerce_broadcasting3(self):
a, b, c = dshapes('10, 10, float32', '10, 10, 10, float32', '1, 10, 10, float32')
self.assertGreater(coercion_cost(a, b), coercion_cost(a, c))
def test_coerce_constrained_typevars(self):
a, b, c = dshapes('10, 10, float32', 'X, Y, float64', 'X, X, float64')
self.assertGreater(coercion_cost(a, b), coercion_cost(a, c))
def test_coercion_transitivity(self):
a, b, c = dshapes('int8', 'complex128', 'float64')
self.assertGreater(coercion_cost(a, b), coercion_cost(a, c))
def test_coerce_numeric(self):
a, b = dshapes('float32', 'float64')
self.assertGreater(coercion_cost(a, b), 0)
def test_coerce_ctype(self):
a, b, c = dshapes('float32', 'float32', 'float64')
self.assertLess(coercion_cost(a, b), coercion_cost(a, c))
def test_coerce_numeric(self):
a, b = dshapes('float32', 'float64')
self.assertEqual(coercion_cost(a, b), 1)
def test_coerce_ctype(self):
a, b = dshapes('float32', 'float32')
self.assertEqual(coercion_cost(a, b), 0)
