def abs_(typesystem, node, x):
from . import builtinmodule
argtype = get_type(x)
nodes.annotate(typesystem.env, node, is_math=True)
if argtype.is_array and argtype.dtype.is_numeric:
# Handle np.abs() on arrays
dtype = builtinmodule.abstype(argtype.dtype)
result_type = argtype.add('dtype', dtype)
node.variable = Variable(result_type)
else:
node = builtinmodule.abs_(typesystem, node, x)
return node
def infer_unary_math_call(context, call_node, arg, default_result_type=double):
"Resolve calls to math functions to llvm.log.f32() etc"
# signature is a generic signature, build a correct one
type = get_type(call_node.args[0])
if type.is_numeric and type.kind < default_result_type.kind:
type = default_result_type
elif type.is_array and type.dtype.is_int:
type = type.copy(dtype=double)
# signature = minitypes.FunctionType(return_type=type, args=[type])
# result = nodes.MathNode(py_func, signature, call_node.args[0])
nodes.annotate(context.env, call_node, is_math=True)
call_node.variable = Variable(type)
return call_node
def infer_unary_math_call(context, call_node, arg, default_result_type=double):
"Resolve calls to math functions to llvm.log.f32() etc"
# signature is a generic signature, build a correct one
type = get_type(call_node.args[0])
if type.is_numeric and type.kind < default_result_type.kind:
type = default_result_type
elif type.is_array and type.dtype.is_int:
type = type.copy(dtype=double)
# signature = minitypes.FunctionType(return_type=type, args=[type])
# result = nodes.MathNode(py_func, signature, call_node.args[0])
nodes.annotate(context.env, call_node, is_math=True)
call_node.variable = Variable(type)
return call_node
def abs_(typesystem, node, x):
from . import builtinmodule
argtype = get_type(x)
nodes.annotate(typesystem.env, node, is_math=True)
if argtype.is_array and argtype.dtype.is_numeric:
# Handle np.abs() on arrays
dtype = builtinmodule.abstype(argtype.dtype)
result_type = argtype.add('dtype', dtype)
node.variable = Variable(result_type)
else:
node = builtinmodule.abs_(typesystem, node, x)
return node
def infer(typesystem, call_node, *args):
"Resolve calls to llvmmath math calls"
# signature is a generic signature, build a correct one
type = reduce(typesystem.promote, map(get_type, call_node.args))
if type.is_numeric and rank(type) < rank(default_result_type):
type = default_result_type
elif type.is_array and type.dtype.is_int:
type = typesystem.array(double, type.ndim)
call_node.args[:] = nodes.CoercionNode.coerce(call_node.args, type)
# TODO: Remove the abuse below
nodes.annotate(typesystem.env, call_node, is_math=True)
call_node.variable = Variable(type)
return call_node
def infer(typesystem, call_node, *args):
"Resolve calls to llvmmath math calls"
# signature is a generic signature, build a correct one
type = reduce(typesystem.promote, map(get_type, call_node.args))
if type.is_numeric and rank(type) < rank(default_result_type):
type = default_result_type
elif type.is_array and type.dtype.is_int:
type = typesystem.array(double, type.ndim)
call_node.args[:] = nodes.CoercionNode.coerce(call_node.args, type)
# TODO: Remove the abuse below
nodes.annotate(typesystem.env, call_node, is_math=True)
call_node.variable = Variable(type)
return call_node
def infer_unary_cmath_call(context, call_node, arg):
result = infer_unary_math_call(context, call_node, arg,
default_result_type=complex128)
nodes.annotate(context.env, call_node, is_cmath=True)
return result
def infer_unary_cmath_call(context, call_node, arg):
result = infer_unary_math_call(context, call_node, arg,
default_result_type=complex128)
nodes.annotate(context.env, call_node, is_cmath=True)
return result
