def _load_(self, value, context):
if isinstance(value, bool):
if self.get_options().allow_bool:
return int(value)
else:
raise ValueError()
elif isinstance(value, integer_types):
if self.get_options().jssafe and not (-MAX_SAFE_INTEGER <= value <= MAX_SAFE_INTEGER):
raise ValueError()
return value
elif isinstance(value, float):
if not self.get_options().allow_nan and (math.isnan(value) or math.isinf(value)):
raise ValueError()
return value
else:
raise ValueError()
python类isinf()的实例源码
def _load_(self, value, context):
if isinstance(value, decimal.Decimal):
if not self.get_options().allow_nan and not value.is_finite():
raise ValueError()
return value
elif isinstance(value, text_types):
try:
with decimal.localcontext() as ctx:
ctx.traps[decimal.InvalidOperation] = 1
value = decimal.Decimal(value)
if not self.get_options().allow_nan and not value.is_finite():
raise ValueError()
return value
except decimal.InvalidOperation:
raise ValueError()
elif isinstance(value, integer_types):
return decimal.Decimal(value)
elif isinstance(value, float):
if not self.get_options().allow_nan:
if math.isnan(value) or math.isinf(value):
raise ValueError()
return decimal.Decimal(value)
else:
raise ValueError()
def _load_(self, value, context):
if isinstance(value, complex):
pass
elif isinstance(value, (integer_types, float)):
value = complex(value)
elif isinstance(value, (tuple, list)):
if len(value) != 2:
raise ValueError()
if not isinstance(value[0], (integer_types, float)) or not isinstance(value[1], (integer_types, float)):
raise ValueError()
value = complex(value[0], value[1])
else:
raise ValueError()
if not self.get_options().allow_nan and (cmath.isnan(value) or cmath.isinf(value)):
raise ValueError()
return value
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def test_isinf(self):
self.assertFalse(cmath.isinf(1))
self.assertFalse(cmath.isinf(1j))
self.assertFalse(cmath.isinf(NAN))
self.assertTrue(cmath.isinf(INF))
self.assertTrue(cmath.isinf(complex(INF, 0)))
self.assertTrue(cmath.isinf(complex(0, INF)))
self.assertTrue(cmath.isinf(complex(INF, INF)))
self.assertTrue(cmath.isinf(complex(NAN, INF)))
self.assertTrue(cmath.isinf(complex(INF, NAN)))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
def rAssertAlmostEqual(self, a, b, rel_err = 2e-15, abs_err = 5e-323,
msg=None):
"""Fail if the two floating-point numbers are not almost equal.
Determine whether floating-point values a and b are equal to within
a (small) rounding error. The default values for rel_err and
abs_err are chosen to be suitable for platforms where a float is
represented by an IEEE 754 double. They allow an error of between
9 and 19 ulps.
"""
# special values testing
if math.isnan(a):
if math.isnan(b):
return
self.fail(msg or '{!r} should be nan'.format(b))
if math.isinf(a):
if a == b:
return
self.fail(msg or 'finite result where infinity expected: '
'expected {!r}, got {!r}'.format(a, b))
# if both a and b are zero, check whether they have the same sign
# (in theory there are examples where it would be legitimate for a
# and b to have opposite signs; in practice these hardly ever
# occur).
if not a and not b:
if math.copysign(1., a) != math.copysign(1., b):
self.fail(msg or 'zero has wrong sign: expected {!r}, '
'got {!r}'.format(a, b))
# if a-b overflows, or b is infinite, return False. Again, in
# theory there are examples where a is within a few ulps of the
# max representable float, and then b could legitimately be
# infinite. In practice these examples are rare.
try:
absolute_error = abs(b-a)
except OverflowError:
pass
else:
# test passes if either the absolute error or the relative
# error is sufficiently small. The defaults amount to an
# error of between 9 ulps and 19 ulps on an IEEE-754 compliant
# machine.
if absolute_error <= max(abs_err, rel_err * abs(a)):
return
self.fail(msg or
'{!r} and {!r} are not sufficiently close'.format(a, b))
