def check(self):
np.random.seed(1234)
# Generate values for the arguments
argarr = get_args(self.arg_spec, self.n)
# Check
old_dps, old_prec = mpmath.mp.dps, mpmath.mp.prec
try:
if self.dps is not None:
dps_list = [self.dps]
else:
dps_list = [20]
if self.prec is not None:
mpmath.mp.prec = self.prec
# Proper casting of mpmath input and output types. Using
# native mpmath types as inputs gives improved precision
# in some cases.
if np.issubdtype(argarr.dtype, np.complexfloating):
pytype = mpc2complex
def mptype(x):
return mpmath.mpc(complex(x))
else:
def mptype(x):
return mpmath.mpf(float(x))
def pytype(x):
if abs(x.imag) > 1e-16 * (1 + abs(x.real)):
return np.nan
else:
return mpf2float(x.real)
# Try out different dps until one (or none) works
for j, dps in enumerate(dps_list):
mpmath.mp.dps = dps
try:
assert_func_equal(
self.scipy_func,
lambda *a: pytype(self.mpmath_func(*map(mptype, a))),
argarr,
vectorized=False,
rtol=self.rtol,
atol=self.atol,
ignore_inf_sign=self.ignore_inf_sign,
distinguish_nan_and_inf=self.distinguish_nan_and_inf,
nan_ok=self.nan_ok,
param_filter=self.param_filter)
break
except AssertionError:
if j >= len(dps_list) - 1:
reraise(*sys.exc_info())
finally:
mpmath.mp.dps, mpmath.mp.prec = old_dps, old_prec
def check(self):
np.random.seed(1234)
# Generate values for the arguments
argarr = get_args(self.arg_spec, self.n)
# Check
old_dps, old_prec = mpmath.mp.dps, mpmath.mp.prec
try:
if self.dps is not None:
dps_list = [self.dps]
else:
dps_list = [20]
if self.prec is not None:
mpmath.mp.prec = self.prec
# Proper casting of mpmath input and output types. Using
# native mpmath types as inputs gives improved precision
# in some cases.
if np.issubdtype(argarr.dtype, np.complexfloating):
pytype = mpc2complex
def mptype(x):
return mpmath.mpc(complex(x))
else:
def mptype(x):
return mpmath.mpf(float(x))
def pytype(x):
if abs(x.imag) > 1e-16*(1 + abs(x.real)):
return np.nan
else:
return mpf2float(x.real)
# Try out different dps until one (or none) works
for j, dps in enumerate(dps_list):
mpmath.mp.dps = dps
try:
assert_func_equal(self.scipy_func,
lambda *a: pytype(self.mpmath_func(*map(mptype, a))),
argarr,
vectorized=False,
rtol=self.rtol, atol=self.atol,
ignore_inf_sign=self.ignore_inf_sign,
distinguish_nan_and_inf=self.distinguish_nan_and_inf,
nan_ok=self.nan_ok,
param_filter=self.param_filter)
break
except AssertionError:
if j >= len(dps_list)-1:
reraise(*sys.exc_info())
finally:
mpmath.mp.dps, mpmath.mp.prec = old_dps, old_prec
def check(self):
np.random.seed(1234)
# Generate values for the arguments
if isinstance(self.arg_spec, np.ndarray):
argarr = self.arg_spec.copy()
else:
num_args = len(self.arg_spec)
ms = np.asarray([1.5 if isinstance(arg, ComplexArg) else 1.0
for arg in self.arg_spec])
ms = (self.n**(ms/sum(ms))).astype(int) + 1
argvals = []
for arg, m in zip(self.arg_spec, ms):
argvals.append(arg.values(m))
argarr = np.array(np.broadcast_arrays(*np.ix_(*argvals))).reshape(num_args, -1).T
# Check
old_dps, old_prec = mpmath.mp.dps, mpmath.mp.prec
try:
if self.dps is not None:
dps_list = [self.dps]
else:
dps_list = [20]
if self.prec is not None:
mpmath.mp.prec = self.prec
# Proper casting of mpmath input and output types. Using
# native mpmath types as inputs gives improved precision
# in some cases.
if np.issubdtype(argarr.dtype, np.complexfloating):
pytype = mpc2complex
def mptype(x):
return mpmath.mpc(complex(x))
else:
def mptype(x):
return mpmath.mpf(float(x))
def pytype(x):
if abs(x.imag) > 1e-16*(1 + abs(x.real)):
return np.nan
else:
return mpf2float(x.real)
# Try out different dps until one (or none) works
for j, dps in enumerate(dps_list):
mpmath.mp.dps = dps
try:
assert_func_equal(self.scipy_func,
lambda *a: pytype(self.mpmath_func(*map(mptype, a))),
argarr,
vectorized=False,
rtol=self.rtol, atol=self.atol,
ignore_inf_sign=self.ignore_inf_sign,
distinguish_nan_and_inf=self.distinguish_nan_and_inf,
nan_ok=self.nan_ok,
param_filter=self.param_filter)
break
except AssertionError:
if j >= len(dps_list)-1:
reraise(*sys.exc_info())
finally:
mpmath.mp.dps, mpmath.mp.prec = old_dps, old_prec
def check(self):
np.random.seed(1234)
# Generate values for the arguments
if isinstance(self.arg_spec, np.ndarray):
argarr = self.arg_spec.copy()
else:
num_args = len(self.arg_spec)
ms = np.asarray([
1.5 if isinstance(arg, ComplexArg) else 1.0
for arg in self.arg_spec
])
ms = (self.n**(ms / sum(ms))).astype(int) + 1
argvals = []
for arg, m in zip(self.arg_spec, ms):
argvals.append(arg.values(m))
argarr = np.array(np.broadcast_arrays(*np.ix_(*argvals))).reshape(
num_args, -1).T
# Check
old_dps, old_prec = mpmath.mp.dps, mpmath.mp.prec
try:
if self.dps is not None:
dps_list = [self.dps]
else:
dps_list = [20]
if self.prec is not None:
mpmath.mp.prec = self.prec
# Proper casting of mpmath input and output types. Using
# native mpmath types as inputs gives improved precision
# in some cases.
if np.issubdtype(argarr.dtype, np.complexfloating):
pytype = mpc2complex
def mptype(x):
return mpmath.mpc(complex(x))
else:
def mptype(x):
return mpmath.mpf(float(x))
def pytype(x):
if abs(x.imag) > 1e-16 * (1 + abs(x.real)):
return np.nan
else:
return mpf2float(x.real)
# Try out different dps until one (or none) works
for j, dps in enumerate(dps_list):
mpmath.mp.dps = dps
try:
assert_func_equal(
self.scipy_func,
lambda *a: pytype(self.mpmath_func(*map(mptype, a))),
argarr,
vectorized=False,
rtol=self.rtol,
atol=self.atol,
ignore_inf_sign=self.ignore_inf_sign,
nan_ok=self.nan_ok,
param_filter=self.param_filter)
break
except AssertionError:
if j >= len(dps_list) - 1:
reraise(*sys.exc_info())
finally:
mpmath.mp.dps, mpmath.mp.prec = old_dps, old_prec
