It's an odd confluence of circumstances that makes numpy.float64 behave
this way. The code that causes the problem is this:
sage/structure/coerce.pyx:965 (cpdef canonical_coercion)
elif y_numeric:
try:
sage_parent = py_scalar_parent(type(y))
if sage_parent is None or
sage_parent.has_coerce_map_from(xp):
return y.__class__(x), y
else:
return self.canonical_coercion(x, sage_parent(y))
except (TypeError, ValueError):
self._record_exception()
Some of the relevant facts:
sage: sage.structure.coerce.py_scalar_parent(type(np.float(1)))
Real Double Field
sage: sage.structure.coerce.py_scalar_parent(type(np.float64(1)))
None
but on the other hand, with cython("def isnum(a): return PY_IS_NUMERIC(a)")
sage: isnum(np.float(1))
True
sage: isnum(np.float32(1))
False
sage: isnum(np.float64(1))
True
sage: isnum(np.float128(1))
False
So it seems to be the combination of "float64" being "numeric" but having
no corresponding "sage scalar parent" defined for it. We have
#define PY_IS_NUMERIC(zzz_obj) \
(PyInt_Check(zzz_obj) || PyBool_Check(zzz_obj) ||
PyLong_Check(zzz_obj) || \
PyFloat_Check(zzz_obj) || PyComplex_Check(zzz_obj))
Indeed:
sage: isinstance(np.float64(1),float)
True
sage: isinstance(np.float32(1),float)
False
sage: isinstance(np.float128(1),float)
False
sage: isinstance(np.float(1),float)
True
sage: type(np.float(1))
<type 'float'>
so the problem is that float64 (at least on most machines) inherits from
float but isn't exactly a float.
We can probably solve the problem by changing py_scalar_parent to check
types via "isinstance" rather than comparison by "is". In the process, you
can also type the argument "py_type" to be a "type". That will cause cython
to generate more efficient code for "isinstance".
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