def call(self, space, args_w):
if len(args_w) > 2:
[w_lhs, w_rhs, w_out] = args_w
else:
[w_lhs, w_rhs] = args_w
w_out = None
w_lhs = convert_to_array(space, w_lhs)
w_rhs = convert_to_array(space, w_rhs)
w_ldtype = w_lhs.get_dtype()
w_rdtype = w_rhs.get_dtype()
if w_ldtype.is_str() and w_rdtype.is_str() and \
self.comparison_func:
pass
elif (w_ldtype.is_str() or w_rdtype.is_str()) and \
self.comparison_func and w_out is None:
return space.wrap(False)
elif w_ldtype.is_flexible() or w_rdtype.is_flexible():
if self.comparison_func:
if self.name == 'equal' or self.name == 'not_equal':
res = w_ldtype.eq(space, w_rdtype)
if not res:
return space.wrap(self.name == 'not_equal')
else:
return space.w_NotImplemented
else:
raise oefmt(space.w_TypeError,
'unsupported operand dtypes %s and %s for "%s"',
w_rdtype.get_name(), w_ldtype.get_name(),
self.name)
if self.are_common_types(w_ldtype, w_rdtype):
if not w_lhs.is_scalar() and w_rhs.is_scalar():
w_rdtype = w_ldtype
elif w_lhs.is_scalar() and not w_rhs.is_scalar():
w_ldtype = w_rdtype
calc_dtype = find_binop_result_dtype(space,
w_ldtype, w_rdtype,
promote_to_float=self.promote_to_float,
promote_bools=self.promote_bools)
if (self.int_only and (not w_ldtype.is_int() or
not w_rdtype.is_int() or
not calc_dtype.is_int()) or
not self.allow_bool and (w_ldtype.is_bool() or
w_rdtype.is_bool()) or
not self.allow_complex and (w_ldtype.is_complex() or
w_rdtype.is_complex())):
raise oefmt(space.w_TypeError,
"ufunc '%s' not supported for the input types", self.name)
if space.is_none(w_out):
out = None
elif not isinstance(w_out, W_NDimArray):
raise oefmt(space.w_TypeError, 'output must be an array')
else:
out = w_out
calc_dtype = out.get_dtype()
if self.comparison_func:
res_dtype = descriptor.get_dtype_cache(space).w_booldtype
else:
res_dtype = calc_dtype
if w_lhs.is_scalar() and w_rhs.is_scalar():
arr = self.func(calc_dtype,
w_lhs.get_scalar_value().convert_to(space, calc_dtype),
w_rhs.get_scalar_value().convert_to(space, calc_dtype)
)
if isinstance(out, W_NDimArray):
if out.is_scalar():
out.set_scalar_value(arr)
else:
out.fill(space, arr)
else:
out = arr
return out
new_shape = shape_agreement(space, w_lhs.get_shape(), w_rhs)
new_shape = shape_agreement(space, new_shape, out, broadcast_down=False)
return loop.call2(space, new_shape, self.func, calc_dtype,
res_dtype, w_lhs, w_rhs, out)
def call(self, space, args_w):
if len(args_w) > 2:
[w_lhs, w_rhs, w_out] = args_w
else:
[w_lhs, w_rhs] = args_w
w_out = None
w_lhs = convert_to_array(space, w_lhs)
w_rhs = convert_to_array(space, w_rhs)
w_ldtype = w_lhs.get_dtype()
w_rdtype = w_rhs.get_dtype()
if w_ldtype.is_str_type() and w_rdtype.is_str_type() and \
self.comparison_func:
pass
elif (w_ldtype.is_str_type() or w_rdtype.is_str_type()) and \
self.comparison_func and w_out is None:
return space.wrap(False)
elif (w_ldtype.is_flexible_type() or \
w_rdtype.is_flexible_type()):
raise OperationError(space.w_TypeError, space.wrap(
'unsupported operand dtypes %s and %s for "%s"' % \
(w_rdtype.get_name(), w_ldtype.get_name(),
self.name)))
if self.are_common_types(w_ldtype, w_rdtype):
if not w_lhs.is_scalar() and w_rhs.is_scalar():
w_rdtype = w_ldtype
elif w_lhs.is_scalar() and not w_rhs.is_scalar():
w_ldtype = w_rdtype
if (self.int_only and (not w_ldtype.is_int_type() or not w_rdtype.is_int_type()) or
not self.allow_bool and (w_ldtype.is_bool_type() or w_rdtype.is_bool_type()) or
not self.allow_complex and (w_ldtype.is_complex_type() or w_rdtype.is_complex_type())):
raise OperationError(space.w_TypeError, space.wrap("Unsupported types"))
calc_dtype = find_binop_result_dtype(space,
w_ldtype, w_rdtype,
promote_to_float=self.promote_to_float,
promote_bools=self.promote_bools)
if space.is_none(w_out):
out = None
elif not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError, space.wrap(
'output must be an array'))
else:
out = w_out
calc_dtype = out.get_dtype()
if self.comparison_func:
res_dtype = interp_dtype.get_dtype_cache(space).w_booldtype
else:
res_dtype = calc_dtype
if w_lhs.is_scalar() and w_rhs.is_scalar():
arr = self.func(calc_dtype,
w_lhs.get_scalar_value().convert_to(calc_dtype),
w_rhs.get_scalar_value().convert_to(calc_dtype)
)
if isinstance(out, W_NDimArray):
if out.is_scalar():
out.set_scalar_value(arr)
else:
out.fill(arr)
else:
out = arr
return out
new_shape = shape_agreement(space, w_lhs.get_shape(), w_rhs)
new_shape = shape_agreement(space, new_shape, out, broadcast_down=False)
return loop.call2(space, new_shape, self.func, calc_dtype,
res_dtype, w_lhs, w_rhs, out)
def call(self, space, args_w):
if len(args_w) > 2:
[w_lhs, w_rhs, w_out] = args_w
else:
[w_lhs, w_rhs] = args_w
w_out = None
w_lhs = convert_to_array(space, w_lhs)
w_rhs = convert_to_array(space, w_rhs)
w_ldtype = w_lhs.get_dtype()
w_rdtype = w_rhs.get_dtype()
if w_ldtype.is_str_type() and w_rdtype.is_str_type() and \
self.comparison_func:
pass
elif (w_ldtype.is_str_type() or w_rdtype.is_str_type()) and \
self.comparison_func and w_out is None:
return space.wrap(False)
elif (w_ldtype.is_flexible_type() or \
w_rdtype.is_flexible_type()):
raise OperationError(space.w_TypeError, space.wrap(
'unsupported operand dtypes %s and %s for "%s"' % \
(w_rdtype.get_name(), w_ldtype.get_name(),
self.name)))
if self.are_common_types(w_ldtype, w_rdtype):
if not w_lhs.is_scalar() and w_rhs.is_scalar():
w_rdtype = w_ldtype
elif w_lhs.is_scalar() and not w_rhs.is_scalar():
w_ldtype = w_rdtype
if (self.int_only and
(not w_ldtype.is_int_type() or not w_rdtype.is_int_type())
or not self.allow_bool and
(w_ldtype.is_bool_type() or w_rdtype.is_bool_type())
or not self.allow_complex and
(w_ldtype.is_complex_type() or w_rdtype.is_complex_type())):
raise OperationError(space.w_TypeError,
space.wrap("Unsupported types"))
calc_dtype = find_binop_result_dtype(
space,
w_ldtype,
w_rdtype,
promote_to_float=self.promote_to_float,
promote_bools=self.promote_bools)
if space.is_none(w_out):
out = None
elif not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError,
space.wrap('output must be an array'))
else:
out = w_out
calc_dtype = out.get_dtype()
if self.comparison_func:
res_dtype = interp_dtype.get_dtype_cache(space).w_booldtype
else:
res_dtype = calc_dtype
if w_lhs.is_scalar() and w_rhs.is_scalar():
arr = self.func(calc_dtype,
w_lhs.get_scalar_value().convert_to(calc_dtype),
w_rhs.get_scalar_value().convert_to(calc_dtype))
if isinstance(out, W_NDimArray):
if out.is_scalar():
out.set_scalar_value(arr)
else:
out.fill(arr)
else:
out = arr
return out
new_shape = shape_agreement(space, w_lhs.get_shape(), w_rhs)
new_shape = shape_agreement(space,
new_shape,
out,
broadcast_down=False)
return loop.call2(space, new_shape, self.func, calc_dtype, res_dtype,
w_lhs, w_rhs, out)
