def testBesselIve(self):
self.assertRaises(ValueError, lambda: _bessel_ive(2.0, 1.0))
# Zero is not a supported value for z.
self.assertRaises(tf.errors.InvalidArgumentError,
lambda: self.evaluate(_bessel_ive(1.5, 0.0)))
z = np.logspace(-6, 2, 20).astype(np.float64)
for v in np.float64([-0.5, 0, 0.5, 1, 1.5]):
self.assertAllClose(sp_special.ive(v, z), _bessel_ive(v, z))
def testBesselIve(self):
with self.assertRaisesRegexp(ValueError, r'imprecise for large v'):
_bessel_ive(2.0, 1.0)
# Zero is not a supported value for z.
with self.assertRaisesOpError(r'NaN'):
self.evaluate(_bessel_ive(1.5, 0.0))
z = np.logspace(-6, 2, 20).astype(np.float64)
for v in np.float64([-0.5, 0, 0.5, 1, 1.5]):
self.assertAllClose(sp_special.ive(v, z), _bessel_ive(v, z))
def testBesselIve(self):
self.assertRaises(ValueError, lambda: _bessel_ive(2.0, 1.0))
# Zero is not a supported value for z.
self.assertRaises(tf.errors.InvalidArgumentError,
lambda: self.evaluate(_bessel_ive(1.5, 0.0)))
z = np.logspace(-6, 2, 20).astype(np.float64)
for v in np.float64([-0.5, 0, 0.5, 1, 1.5]):
try:
from scipy import special # pylint:disable=g-import-not-at-top
except ImportError:
tf.logging.warn('Skipping scipy-dependent tests')
return
self.assertAllClose(special.ive(v, z), _bessel_ive(v, z))
