def test_wrapped_func_with_kwargs():
"""
Test wrapped functions with keyword args
"""
def cos_plain(angle):
return math.cos(angle)
def cos_kwargs(angle, **kwargs):
return math.cos(angle)
def use_kwargs(angle, cos=True):
if cos:
return math.cos(angle)
else:
return math.sin(angle)
# wrappings of these functions
wrap_cos_plain = wrap(cos_plain)
wrap_cos_wderiv = wrap(cos_plain, [math.cos])
wrap_cos_kwargs = wrap(cos_kwargs)
wrap_use_kwargs = wrap(use_kwargs)
umath_cos = umath.cos
umath_sin = umath.sin
# now test that the wrapped functions give the same results
# as the umath versions for a variety of input values
for a in (ufloat((0.2, 0.01)), ufloat((0.7, 0.00001)),
#ufloat((0.9, 0.3)), ufloat((1.e-4, 0.3)),
#ufloat((200.0, 0.3)), ufloat((1.e5, 0.3)),
#0, 2, 1.25, 0.0, 1.e-5, 0.707, 1.5708
):
ucos = umath_cos(a)
usin = umath_sin(a)
assert _numbers_close(ucos, wrap_cos_plain(a))
assert _numbers_close(ucos, wrap_cos_wderiv(a))
assert _numbers_close(ucos, wrap_cos_kwargs(a))
assert _numbers_close(ucos, wrap_cos_kwargs(a, opt=None))
assert _numbers_close(ucos, wrap_cos_kwargs(a, opt=None, opt2=True))
assert _numbers_close(ucos, wrap_use_kwargs(a, cos=True))
assert _numbers_close(usin, wrap_use_kwargs(a, cos=False))
# affirm that calling a wrapped function with unsupported
# keyword args raises a TypeError
raised = False
try:
wrap_use_kwargs(a, other=False)
except TypeError:
raised = True
assert raised
def wrapped_fsum():
"""
Returns an uncertainty-aware version of math.fsum, which must
be contained in _original_func.
"""
# The fsum function is flattened, in order to use the
# wrap() wrapper:
flat_fsum = lambda *args: original_func(args)
flat_fsum_wrap = wrap(flat_fsum, itertools.repeat(lambda *args: 1))
return wraps(lambda arg_list: flat_fsum_wrap(*arg_list), original_func)
def wrapped_fsum():
"""
Returns an uncertainty-aware version of math.fsum, which must
be contained in _original_func.
"""
# The fsum function is flattened, in order to use the
# wrap() wrapper:
flat_fsum = lambda *args: original_func(args)
flat_fsum_wrap = wrap(
flat_fsum, itertools.repeat(lambda *args: 1))
return wraps(lambda arg_list: flat_fsum_wrap(*arg_list),
original_func)
def test_wrapped_func():
"""
Test uncertainty-aware functions obtained through wrapping.
"""
# This function can be wrapped so that it works when 'angle' has
# an uncertainty (math.cos does not handle numbers with
# uncertainties):
def f(angle, list_var):
return math.cos(angle) + sum(list_var)
f_wrapped = wrap(f)
my_list = [1, 2, 3]
# Test of a wrapped function that only calls the original function:
assert f_wrapped(0, my_list) == 1 + sum(my_list)
# As a precaution, the wrapped function does not venture into
# calculating f with uncertainties when one of the argument is not
# a simple number, because this argument might contain variables:
angle = ufloat((0, 0.1))
assert f_wrapped(angle, [angle, angle]) == NotImplemented
assert f_wrapped(angle, my_list) == NotImplemented
# for (name, attr) in vars(math).items():
for name in dir(math):
if name in fixed_derivatives: # Priority to functions in fixed_derivatives
derivatives = fixed_derivatives[name]
elif name in num_deriv_funcs:
# Functions whose derivatives are calculated numerically by
# this module fall here (isinf, fmod,...):
derivatives = None # Means: numerical calculation required
else:
continue # 'name' not wrapped by this module (__doc__, e, etc.)
func = getattr(math, name)
setattr(this_module, name, wraps(wrap(func, derivatives), func))
many_scalars_to_scalar_funcs.append(name)
###############################################################################
########################################
# Special cases: some of the functions from no_std_wrapping:
##########
# The math.factorial function is not converted to an uncertainty-aware
# function, because it does not handle non-integer arguments: it does
# not make sense to give it an argument with a numerical error
# (whereas this would be relevant for the gamma function).
##########
# for (name, attr) in vars(math).items():
for name in dir(math):
if name in fixed_derivatives: # Priority to functions in fixed_derivatives
derivatives = fixed_derivatives[name]
elif name in num_deriv_funcs:
# Functions whose derivatives are calculated numerically by
# this module fall here (isinf, fmod,...):
derivatives = None # Means: numerical calculation required
else:
continue # 'name' not wrapped by this module (__doc__, e, etc.)
func = getattr(math, name)
setattr(this_module, name,
wraps(wrap(func, derivatives), func))
many_scalars_to_scalar_funcs.append(name)
###############################################################################
########################################
# Special cases: some of the functions from no_std_wrapping:
##########
# The math.factorial function is not converted to an uncertainty-aware
# function, because it does not handle non-integer arguments: it does
# not make sense to give it an argument with a numerical error
# (whereas this would be relevant for the gamma function).
##########
