org.pycforge.math · Author: PyCForge
License: GPL-3.0-only · Created: 2026-10-28
Runtime conversion · Direct declared calls
acos · acosh · asin · asinh · atan · atan2 · atanh · cbrt · ceil · copysign · cos · cosh · erf · erfc · exp · exp2 · expm1 · fabs · floor · fmod · isclose · isfinite · isinf · isnan · log · log10 · log1p · log2 · pow · remainder · sin · sinh · sqrt · tan · tanh · trunc
Thirty-six scalar math functions and five binary64 constants, converted through public Crucible contracts.
Select Runtime. Declare *import math as m at the top of the module, then use direct calls such as m.sin(0.0) or constants such as m.pi. Trigonometric input angles are radians. Use m.log(8, 2) for base-two logarithms and m.isclose(a=1.0, b=1.0000000001, rel_tol=1e-9) for tolerance comparisons. See each signature below.
This package covers only the listed exports and call shapes. log takes one or two positional arguments. isclose accepts named a/b and keyword-only rel_tol/abs_tol; other exports remain positional-only. Unpacking, first-class function values, arrays and NumPy are unsupported. floor, ceil and trunc return bounded int64, unlike Python's arbitrary-precision integer results. Native libm results depend on the compiler and platform; cross-platform bit identity and NaN payload identity are not promised. Runtime remains a preview target.
0.3.0 adds optional-base log and isclose through scalar profile 0.3 parameter and reusable kernel contracts. Existing positional calls remain supported.
Examples are author-supplied fixture snapshots. The SDK reports verification for its recorded environment; PyCForge registration does not rerun them.
Use *import math in the module preamble. Each signature states accepted positions, names and defaults. A slash marks positional-only parameters; a star marks keyword-only parameters. Argument expansion, function values and Typed conversion are unsupported.
Inputs: bool, signed int64 or float64. Native numeric operands use binary64 C double. Wrong runtime value types raise TypeError; runtime exceptions remain catchable. C11 math.h, default rounding, no fast-math; POSIX linking uses -lm. No arrays or arbitrary-precision results.
Inverse cosine; input from -1 through 1
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand outside [-1, 1] raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse cosine; input from -1 through 1. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Cosine value in the closed interval [-1, 1].
Returns: Principal inverse cosine in radians.
Inverse hyperbolic cosine; input at least 1
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand below 1 raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse hyperbolic cosine; input at least 1. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic cosine value at least one.
Returns: Nonnegative inverse hyperbolic cosine.
Inverse sine; input from -1 through 1
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand outside [-1, 1] raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse sine; input from -1 through 1. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Sine value in the closed interval [-1, 1].
Returns: Principal inverse sine in radians.
Inverse hyperbolic sine
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse hyperbolic sine. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic sine value.
Returns: Inverse hyperbolic sine.
Inverse tangent
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse tangent. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Tangent value.
Returns: Principal inverse tangent in radians.
Angle of the vector (second input, first input)
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Angle of the vector (second input, first input). The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Vertical coordinate y.
Argument 2: Horizontal coordinate x.
Returns: Angle in radians with the quadrant determined by both coordinates.
Inverse hyperbolic tangent; input strictly between -1 and 1
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand outside (-1, 1) raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Inverse hyperbolic tangent; input strictly between -1 and 1. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic tangent value strictly between -1 and 1.
Returns: Inverse hyperbolic tangent.
Real cube root
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Real cube root. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number whose real cube root is requested.
Returns: Real cube root, with negative roots for negative inputs.
Smallest integer no less than input; result must fit int64
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Result must fit signed int64; nonfinite or out-of-range results raise an exception.
Existing bool/int64 operands retain their exact integer value.
Smallest integer no less than input; result must fit int64. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to round upward.
Returns: Smallest integer no less than the input, within signed int64.
Magnitude of the first input with the sign of the second
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: direct native result after the declared input guards.
Magnitude of the first input with the sign of the second. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number supplying the magnitude.
Argument 2: Number supplying the sign, including the sign of zero.
Returns: Magnitude of the first argument with the sign of the second.
Cosine in radians
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Either infinity in the first operand raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Cosine in radians. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Angle in radians.
Returns: Cosine of the angle.
Hyperbolic cosine with overflow checking
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Hyperbolic cosine with overflow checking. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic angle.
Returns: Hyperbolic cosine.
Error function
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Error function. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Real argument to the error function.
Returns: Value of the native error function.
Complementary error function
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Complementary error function. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Real argument to the complementary error function.
Returns: Complementary error-function value, computed directly by the native operation.
Exponential with overflow checking
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Exponential with overflow checking. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Exponent for base e.
Returns: e raised to the supplied exponent.
Base-two exponential with overflow checking
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Base-two exponential with overflow checking. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Exponent for base two.
Returns: Two raised to the supplied exponent.
Exponential minus one, accurate near zero
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Exponential minus one, accurate near zero. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Exponent for base e.
Returns: exp(x) minus one, using the native operation intended for accuracy near zero.
Floating-point absolute value
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: direct native result after the declared input guards.
Floating-point absolute value. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number whose magnitude is requested.
Returns: Absolute value as float64.
Largest integer no greater than input; result must fit int64
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Result must fit signed int64; nonfinite or out-of-range results raise an exception.
Existing bool/int64 operands retain their exact integer value.
Largest integer no greater than input; result must fit int64. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to round downward.
Returns: Largest integer no greater than the input, within signed int64.
Floating remainder with the sign of the first input
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Exactly two operands. Unless either is NaN, reject an infinite first operand or zero second operand.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Floating remainder with the sign of the first input. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Dividend.
Argument 2: Divisor.
Returns: Floating remainder with the dividend's sign, following the native fmod operation.
Symmetric relative or absolute closeness with optional keyword-only tolerances
a: positional-or-keyword; required
b: positional-or-keyword; required
rel_tol: keyword-only; default 1e-09
abs_tol: keyword-only; default 0.0
Four slots: left, right, relative tolerance, absolute tolerance. Convert all to binary64; negative tolerances raise ValueError before equality. Equal values, including matching infinities, return True. Other infinite operands return False. Otherwise compare abs(right-left) to abs(relative*right), abs(relative*left), or absolute. NaN operands are never close; NaN tolerances participate in ordinary comparisons. Tolerances greater than or equal to 1 and positive infinity are accepted, matching CPython 3.12 behavior.
Symmetric relative or absolute closeness with optional keyword-only tolerances. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: First value a, positional or named.
Argument 2: Second value b, positional or named.
Argument 3: Keyword-only relative tolerance; defaults to 1e-9. Negative values raise ValueError.
Argument 4: Keyword-only absolute tolerance; defaults to 0.0. Negative values raise ValueError.
Returns: True for equal values or a difference within either symmetric relative bound or the absolute bound. NaN operands are never close; infinities are close only to themselves.
Test whether an input is finite
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: direct native result after the declared input guards.
Test whether an input is finite. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to classify.
Returns: True for finite numbers; False for infinities and NaN.
Test whether an input is an infinity
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: direct native result after the declared input guards.
Test whether an input is an infinity. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to classify.
Returns: True for either positive or negative infinity.
Test whether an input is NaN
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: direct native result after the declared input guards.
Test whether an input is NaN. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to classify.
Returns: True for NaN.
Natural logarithm or logarithm to an optional positional base
x: positional-only; required
base: positional-only; default omitted
Two slots: value and optional base with omitted default. Check and log the first value before checking the base. Nonpositive values raise ValueError; explicit None raises TypeError. Omission returns log(value); otherwise return log(value)/log(base). Base 1 raises ZeroDivisionError, including a NaN numerator. NaN and infinities propagate through the quotient; signed zero and underflow follow binary64. No arbitrary-precision integer logarithms.
Natural logarithm or logarithm to an optional positional base. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Strictly positive value; NaN propagates.
Argument 2: Optional positional base. Omit for the natural logarithm; nonpositive bases raise ValueError, base 1 raises ZeroDivisionError, and explicit None raises TypeError.
Returns: Natural logarithm when base is omitted, otherwise log(value)/log(base).
Base-ten logarithm; positive input
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand at or below zero raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Base-ten logarithm; positive input. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Strictly positive number.
Returns: Base-ten logarithm.
Natural logarithm of one plus input; input greater than -1
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand at or below -1 raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Natural logarithm of one plus input; input greater than -1. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number strictly greater than -1.
Returns: Natural logarithm of one plus the supplied number.
Base-two logarithm; positive input
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand at or below zero raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Base-two logarithm; positive input. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Strictly positive number.
Returns: Base-two logarithm.
Floating-point power with domain and overflow checking
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Exactly two operands. For finite operands, reject zero to a negative power and a negative base to a nonintegral power. Nonfinite cases follow the native operation.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Floating-point power with domain and overflow checking. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Base.
Argument 2: Exponent.
Returns: Floating-point power subject to the real-power domain guard.
IEEE remainder using the nearest even quotient
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Exactly two operands. Unless either is NaN, reject an infinite first operand or zero second operand.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
IEEE remainder using the nearest even quotient. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Dividend.
Argument 2: Divisor.
Returns: IEEE remainder computed using the nearest integer quotient, with ties to even.
View example: native-remainder
Sine in radians
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Either infinity in the first operand raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Sine in radians. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Angle in radians.
Returns: Sine of the angle.
Hyperbolic sine with overflow checking
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Hyperbolic sine with overflow checking. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic angle.
Returns: Hyperbolic sine.
Square root; negative inputs raise ValueError
Argument labels indicate positions; they are not accepted keyword names.
Input domain: First operand below zero raises ValueError; negative zero and NaN pass.
Native error policy: direct native result after the declared input guards.
Square root; negative inputs raise ValueError. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Nonnegative number; negative zero is accepted.
Returns: Square root as float64.
Tangent in radians
Argument labels indicate positions; they are not accepted keyword names.
Input domain: Either infinity in the first operand raises ValueError; NaN passes.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Tangent in radians. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Angle in radians.
Returns: Tangent of the angle.
Hyperbolic tangent
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Hyperbolic tangent. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Hyperbolic angle.
Returns: Hyperbolic tangent.
Integer part toward zero; result must fit int64
Argument labels indicate positions; they are not accepted keyword names.
Input domain: No additional input-domain restriction after numeric type checks.
Native error policy: checked domain/range errors; overflow raises OverflowError and underflow is permitted.
Result must fit signed int64; nonfinite or out-of-range results raise an exception.
Existing bool/int64 operands retain their exact integer value.
Integer part toward zero; result must fit int64. The example exercises representative values and exception cases; the generated contract below states the supported domain and result limits.
Argument 1: Number to truncate toward zero.
Returns: Integer part toward zero, within signed int64.
*import math as m
def checked(x):
try:
value = m.acos(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.5707963267948966 1.0 0.0 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 3.141592653589793 1.0 0.0 1.0 ValueError ValueError 2.0943951023931957 1.0 1.0471975511965979 1.0 ValueError 3.141592638688632 1.0 1.4901161193847656e-08 1.0 ValueError 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.acosh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
ValueError 0.0 1.0 ValueError ValueError ValueError 0.0 1.0 ValueError 1.3169578969248166 1.0 ValueError ValueError ValueError ValueError ValueError 2.1073424255447017e-08 1.0 ValueError ValueError ValueError ValueError ValueError 7.600902209541989 1.0 ValueError 691.4686750787736 1.0 44.3614195558365 1.0 ValueError inf 1.0 ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.asin(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.5707963267948966 1.0 -0.0 -1.0 0.0 1.0 -1.5707963267948966 -1.0 1.5707963267948966 1.0 ValueError ValueError -0.5235987755982989 -1.0 0.5235987755982989 1.0 ValueError -1.5707963118937354 -1.0 1.5707963118937354 1.0 ValueError -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.asinh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.881373587019543 1.0 -0.0 -1.0 0.0 1.0 -0.881373587019543 -1.0 0.881373587019543 1.0 -1.4436354751788103 -1.0 1.4436354751788103 1.0 -0.48121182505960347 -1.0 0.48121182505960347 1.0 -0.8813735870195432 -1.0 -0.8813735870195429 -1.0 0.8813735870195429 1.0 0.8813735870195432 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -7.600902709541988 -1.0 7.600902709541988 1.0 -691.4686750787736 -1.0 691.4686750787736 1.0 44.3614195558365 1.0 -44.3614195558365 -1.0 inf 1.0 -inf -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.atan(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.7853981633974483 1.0 -0.0 -1.0 0.0 1.0 -0.7853981633974483 -1.0 0.7853981633974483 1.0 -1.1071487177940904 -1.0 1.1071487177940904 1.0 -0.4636476090008061 -1.0 0.4636476090008061 1.0 -0.7853981633974484 -1.0 -0.7853981633974483 -1.0 0.7853981633974483 1.0 0.7853981633974484 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -1.5697963271282298 -1.0 1.5697963271282298 1.0 -1.5707963267948966 -1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 -1.5707963267948966 -1.0 1.5707963267948966 1.0 -1.5707963267948966 -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.atan2(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
0.0 1.0 0.0 1.0 3.141592653589793 1.0 3.141592653589793 1.0 3.141592653589793 1.0 3.141592653589793 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 3.141592653589793 1.0 0.0 1.0 3.141592653589793 1.0 0.0 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 0.7853981633974483 1.0 3.0309354324158977 1.0 2.677945044588987 1.0 2.356194490192345 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.1071487177940904 1.0 0.7853981633974483 1.0 0.4636476090008061 1.0 0.3217505543966422 1.0 3.141592653589793 1.0 1e-300 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan -1.5707963267948966 -1.0 -1.460139105621001 -1.0 -2.356194490192345 -1.0 -1.7894652726688385 -1.0 -1.6814535479687922 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5152978215491797 -1.0 -1.460139105621001 -1.0 -1.3521273809209546 -1.0 -1.2490457723982544 -1.0 -3.141592653589793 -1.0 -9e-300 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan -1.5707963267948966 -1.0 -1.1071487177940904 -1.0 -2.922923707715851 -1.0 -2.356194490192345 -1.0 -2.0344439357957027 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.3258176636680326 -1.0 -1.1071487177940904 -1.0 -0.7853981633974483 -1.0 -0.5880026035475675 -1.0 -3.141592653589793 -1.0 -2e-300 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan -1.5707963267948966 -1.0 -0.7853981633974483 -1.0 -3.0309354324158977 -1.0 -2.677945044588987 -1.0 -2.356194490192345 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.1071487177940904 -1.0 -0.7853981633974483 -1.0 -0.4636476090008061 -1.0 -0.3217505543966422 -1.0 -3.141592653589793 -1.0 -1e-300 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan -0.0 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 -3.141592653589793 -1.0 -3.141592653589793 -1.0 -3.141592653589793 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 -0.0 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan 0.0 1.0 0.0 1.0 3.141592653589793 1.0 3.141592653589793 1.0 3.141592653589793 1.0 3.141592653589793 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 3.141592653589793 1.0 0.0 1.0 3.141592653589793 1.0 0.0 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 0.4636476090008061 1.0 3.0860941483440762 1.0 2.896613990462929 1.0 2.677945044588987 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.7853981633974483 1.0 0.4636476090008061 1.0 0.24497866312686414 1.0 0.16514867741462683 1.0 3.141592653589793 1.0 5e-301 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 0.7853981633974483 1.0 3.0309354324158977 1.0 2.677945044588987 1.0 2.356194490192345 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.1071487177940904 1.0 0.7853981633974483 1.0 0.4636476090008061 1.0 0.3217505543966422 1.0 3.141592653589793 1.0 1e-300 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 1.1071487177940904 1.0 2.922923707715851 1.0 2.356194490192345 1.0 2.0344439357957027 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.3258176636680326 1.0 1.1071487177940904 1.0 0.7853981633974483 1.0 0.5880026035475675 1.0 3.141592653589793 1.0 2e-300 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 1.2490457723982544 1.0 2.819842099193151 1.0 2.158798930342464 1.0 1.892546881191539 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.4056476493802699 1.0 1.2490457723982544 1.0 0.982793723247329 1.0 0.7853981633974483 1.0 3.141592653589793 1.0 2.9999999999999996e-300 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -2.356194490192345 -1.0 -0.7853981633974483 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 2.356194490192345 1.0 0.7853981633974483 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.0 1.0 3.141592653589793 1.0 nan -1.5707963267948966 -1.0 -5e-324 -1.0 -3.141592653589793 -1.0 -3.141592653589793 -1.0 -3.141592653589793 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1e-323 -1.0 -5e-324 -1.0 -0.0 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 -0.0 -1.0 -2.356194490192345 -1.0 -0.7853981633974483 -1.0 -0.0 -1.0 -3.141592653589793 -1.0 nan 1.5707963267948966 1.0 5e-324 1.0 3.141592653589793 1.0 3.141592653589793 1.0 3.141592653589793 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1e-323 1.0 5e-324 1.0 0.0 1.0 0.0 1.0 3.141592653589793 1.0 0.0 1.0 2.356194490192345 1.0 0.7853981633974483 1.0 0.0 1.0 3.141592653589793 1.0 nan 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 1.5707963267948966 1.0 0.7853981633974483 1.0 2.356194490192345 1.0 nan -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -1.5707963267948966 -1.0 -0.7853981633974483 -1.0 -2.356194490192345 -1.0 nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.atanh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 ValueError -0.0 -1.0 0.0 1.0 ValueError ValueError ValueError ValueError -0.5493061443340548 -1.0 0.5493061443340548 1.0 ValueError -18.714973875118524 -1.0 18.714973875118524 1.0 ValueError -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.cbrt(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.0 1.0 -0.0 -1.0 0.0 1.0 -1.0 -1.0 1.0 1.0 -1.2599210498948734 -1.0 1.2599210498948734 1.0 -0.7937005259840998 -1.0 0.7937005259840998 1.0 -1.0 -1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.7031839360032601e-108 -1.0 1.7031839360032601e-108 1.0 -1e-100 -1.0 1e-100 1.0 -10.0 -1.0 10.0 1.0 -1e+100 -1.0 1e+100 1.0 2097152.0 1.0 -2097152.0 -1.0 inf 1.0 -inf -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.ceil(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1.5, 1.5, -0.1, 0.1, -5e-324, 5e-324, 9007199254740993, -9007199254740993, 9223372036854775807, -9223372036854775808, 9223372036854774784.0, -9223372036854775808.0, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0 1 0 0 -1 2 0 1 0 1 9007199254740993 -9007199254740993 9223372036854775807 -9223372036854775808 9223372036854774784 -9223372036854775808 OverflowError OverflowError ValueError TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.copysign(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
0.0 1.0 0.0 1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 9.0 1.0 9.0 1.0 -9.0 -1.0 -9.0 -1.0 -9.0 -1.0 -9.0 -1.0 9.0 1.0 9.0 1.0 9.0 1.0 9.0 1.0 9.0 1.0 -9.0 -1.0 9.0 1.0 -9.0 -1.0 9.0 1.0 9.0 1.0 -9.0 -1.0 9.0 1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 -2.0 -1.0 -2.0 -1.0 -2.0 -1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 0.5 1.0 0.5 1.0 -0.5 -1.0 -0.5 -1.0 -0.5 -1.0 -0.5 -1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 -0.5 -1.0 0.5 1.0 -0.5 -1.0 0.5 1.0 0.5 1.0 -0.5 -1.0 0.5 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 -2.0 -1.0 -2.0 -1.0 -2.0 -1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 2.0 1.0 -2.0 -1.0 2.0 1.0 3.0 1.0 3.0 1.0 -3.0 -1.0 -3.0 -1.0 -3.0 -1.0 -3.0 -1.0 3.0 1.0 3.0 1.0 3.0 1.0 3.0 1.0 3.0 1.0 -3.0 -1.0 3.0 1.0 -3.0 -1.0 3.0 1.0 3.0 1.0 -3.0 -1.0 3.0 1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 -1e+300 -1.0 -1e+300 -1.0 -1e+300 -1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 -1e+300 -1.0 -1e+300 -1.0 -1e+300 -1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 1e+300 1.0 -1e+300 -1.0 1e+300 1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 5e-324 1.0 -5e-324 -1.0 5e-324 1.0 inf 1.0 inf 1.0 -inf -1.0 -inf -1.0 -inf -1.0 -inf -1.0 inf 1.0 inf 1.0 inf 1.0 inf 1.0 inf 1.0 -inf -1.0 inf 1.0 -inf -1.0 inf 1.0 inf 1.0 -inf -1.0 inf 1.0 inf 1.0 inf 1.0 -inf -1.0 -inf -1.0 -inf -1.0 -inf -1.0 inf 1.0 inf 1.0 inf 1.0 inf 1.0 inf 1.0 -inf -1.0 inf 1.0 -inf -1.0 inf 1.0 inf 1.0 -inf -1.0 inf 1.0 nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.cos(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.0 1.0 0.5403023058681398 1.0 1.0 1.0 1.0 1.0 0.5403023058681398 1.0 0.5403023058681398 1.0 -0.4161468365471424 -1.0 -0.4161468365471424 -1.0 0.8775825618903728 1.0 0.8775825618903728 1.0 0.5403023058681395 1.0 0.5403023058681398 1.0 0.5403023058681398 1.0 0.5403023058681395 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.5623790762907029 1.0 0.5623790762907029 1.0 -0.5753861119575491 -1.0 -0.5753861119575491 -1.0 0.011800076512800236 1.0 0.011800076512800236 1.0 ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.cosh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.0 1.0 1.5430806348152437 1.0 1.0 1.0 1.0 1.0 1.5430806348152437 1.0 1.5430806348152437 1.0 3.7621956910836314 1.0 3.7621956910836314 1.0 1.1276259652063807 1.0 1.1276259652063807 1.0 1.5430806348152442 1.0 1.5430806348152437 1.0 1.5430806348152437 1.0 1.5430806348152442 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 OverflowError OverflowError OverflowError OverflowError OverflowError OverflowError inf 1.0 inf 1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.erf(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.8427007929497149 1.0 -0.0 -1.0 0.0 1.0 -0.8427007929497149 -1.0 0.8427007929497149 1.0 -0.9953222650189527 -1.0 0.9953222650189527 1.0 -0.5204998778130465 -1.0 0.5204998778130465 1.0 -0.842700792949715 -1.0 -0.8427007929497148 -1.0 0.8427007929497148 1.0 0.842700792949715 1.0 -5e-324 -1.0 5e-324 1.0 -1.1283791670955126e-300 -1.0 1.1283791670955126e-300 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.erfc(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.0 1.0 0.15729920705028513 1.0 1.0 1.0 1.0 1.0 1.842700792949715 1.0 0.15729920705028513 1.0 1.9953222650189528 1.0 0.004677734981047265 1.0 1.5204998778130465 1.0 0.4795001221869535 1.0 1.842700792949715 1.0 1.8427007929497148 1.0 0.1572992070502852 1.0 0.15729920705028505 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 2.0 1.0 0.0 1.0 2.0 1.0 0.0 1.0 0.0 1.0 2.0 1.0 0.0 1.0 2.0 1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.exp(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.0 1.0 2.718281828459045 1.0 1.0 1.0 1.0 1.0 0.36787944117144233 1.0 2.718281828459045 1.0 0.1353352832366127 1.0 7.38905609893065 1.0 0.6065306597126334 1.0 1.6487212707001282 1.0 0.3678794411714422 1.0 0.3678794411714424 1.0 2.718281828459045 1.0 2.718281828459046 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 OverflowError 0.0 1.0 OverflowError OverflowError 0.0 1.0 inf 1.0 0.0 1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.exp2(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
1.0 1.0 2.0 1.0 1.0 1.0 1.0 1.0 0.5 1.0 2.0 1.0 0.25 1.0 4.0 1.0 0.7071067811865476 1.0 1.4142135623730951 1.0 0.49999999999999994 1.0 0.5 1.0 1.9999999999999998 1.0 2.0000000000000004 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 9.332636185032189e-302 1.0 1.0715086071862673e+301 1.0 0.0 1.0 OverflowError OverflowError 0.0 1.0 inf 1.0 0.0 1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.expm1(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.718281828459045 1.0 -0.0 -1.0 0.0 1.0 -0.6321205588285577 -1.0 1.718281828459045 1.0 -0.8646647167633873 -1.0 6.38905609893065 1.0 -0.3934693402873666 -1.0 0.6487212707001282 1.0 -0.6321205588285578 -1.0 -0.6321205588285577 -1.0 1.7182818284590449 1.0 1.718281828459046 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -1.0 -1.0 OverflowError -1.0 -1.0 OverflowError OverflowError -1.0 -1.0 inf 1.0 -1.0 -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.fabs(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 2.0 1.0 2.0 1.0 0.5 1.0 0.5 1.0 1.0000000000000002 1.0 0.9999999999999999 1.0 0.9999999999999999 1.0 1.0000000000000002 1.0 5e-324 1.0 5e-324 1.0 1e-300 1.0 1e-300 1.0 1000.0 1.0 1000.0 1.0 1e+300 1.0 1e+300 1.0 9.223372036854776e+18 1.0 9.223372036854776e+18 1.0 inf 1.0 inf 1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.floor(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1.5, 1.5, -0.1, 0.1, -5e-324, 5e-324, 9007199254740993, -9007199254740993, 9223372036854775807, -9223372036854775808, 9223372036854774784.0, -9223372036854775808.0, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0 1 0 0 -2 1 -1 0 -1 0 9007199254740993 -9007199254740993 9223372036854775807 -9223372036854775808 9223372036854774784 -9223372036854775808 OverflowError OverflowError ValueError TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.fmod(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 nan ValueError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -0.0 -1.0 -9.0 -1.0 -9.0 -1.0 -0.0 -1.0 -0.0 -1.0 -9.0 -1.0 -9.0 -1.0 nan ValueError -0.0 -1.0 -2.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -2.0 -1.0 -2.0 -1.0 -2.0 -1.0 -0.0 -1.0 -0.0 -1.0 -2.0 -1.0 -2.0 -1.0 nan ValueError -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 nan ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 nan ValueError 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 ValueError ValueError 0.0 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.0 1.0 0.0 1.0 0.5 1.0 0.5 1.0 nan ValueError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 nan ValueError 0.0 1.0 2.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 2.0 1.0 2.0 1.0 2.0 1.0 0.0 1.0 0.0 1.0 2.0 1.0 2.0 1.0 nan ValueError 0.0 1.0 3.0 1.0 1.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 1.0 1.0 0.0 1.0 3.0 1.0 3.0 1.0 0.0 1.0 0.0 1.0 3.0 1.0 3.0 1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -1e+300 -1.0 -1e+300 -1.0 nan ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 1e+300 1.0 1e+300 1.0 nan ValueError -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 ValueError ValueError -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -0.0 -1.0 -0.0 -1.0 -5e-324 -1.0 -5e-324 -1.0 nan ValueError 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 ValueError ValueError 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 0.0 1.0 0.0 1.0 5e-324 1.0 5e-324 1.0 nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.isclose(x, y)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
True False False False False True True False False False False False False False False False False False False True False False False False False False True False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False True False False False False True True False False False False False False False False False False False True False False False False True True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False True False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False True False False False False False False False False False False False False False False False False False False False TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.isfinite(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
True True True True True True True True True True True True True True True True True True True True True True True True False False False TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.isinf(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
False False False False False False False False False False False False False False False False False False False False False False False False True True False TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.isnan(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
False False False False False False False False False False False False False False False False False False False False False False False False False False True TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.log(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
print(m.log(1), m.log(m.e), m.log(m.inf))
return 0
Expected standard output:
ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -0.0 -1.0 ZeroDivisionError 0.0 1.0 0.0 1.0 ValueError 0.0 1.0 ValueError -0.0 -1.0 0.0 1.0 ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError 1.0 1.0 ZeroDivisionError -1.0 -1.0 -0.6309297535714574 -1.0 ValueError -0.0010034333188799374 -1.0 ValueError 0.000931098696461825 1.0 -0.0 -1.0 ValueError nan ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -0.0 -1.0 ZeroDivisionError 0.0 1.0 0.0 1.0 ValueError 0.0 1.0 ValueError -0.0 -1.0 0.0 1.0 ValueError nan ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -1.0 -1.0 ZeroDivisionError 1.0 1.0 0.6309297535714574 1.0 ValueError 0.0010034333188799374 1.0 ValueError -0.000931098696461825 -1.0 0.0 1.0 ValueError nan ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -1.5849625007211563 -1.0 ZeroDivisionError 1.5849625007211563 1.0 1.0 1.0 ValueError 0.001590404182398875 1.0 ValueError -0.001475756518362343 -1.0 0.0 1.0 ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -996.5784284662087 -1.0 ZeroDivisionError 996.5784284662087 1.0 628.7709822868153 1.0 ValueError 1.0 1.0 ValueError -0.927912875666861 -1.0 0.0 1.0 ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError 1074.0 1.0 ZeroDivisionError -1074.0 -1.0 -677.6185553357452 -1.0 ValueError -1.0776873844770527 -1.0 ValueError 1.0 1.0 -0.0 -1.0 ValueError nan ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError -inf -1.0 ZeroDivisionError inf 1.0 inf 1.0 ValueError inf 1.0 ValueError -inf -1.0 nan ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ZeroDivisionError ValueError ValueError ValueError ValueError ValueError nan ZeroDivisionError nan nan ValueError nan ValueError nan nan ValueError nan TypeError TypeError TypeError TypeError 0.0 1.0 inf
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.log10(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
ValueError 0.0 1.0 ValueError ValueError ValueError 0.0 1.0 ValueError 0.3010299956639812 1.0 ValueError -0.3010299956639812 -1.0 ValueError ValueError -4.8216373327664354e-17 -1.0 9.64327466553287e-17 1.0 ValueError -323.3062153431158 -1.0 ValueError -300.0 -1.0 ValueError 3.0 1.0 ValueError 300.0 1.0 18.964889726830815 1.0 ValueError inf 1.0 ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.log1p(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.6931471805599453 1.0 -0.0 -1.0 0.0 1.0 ValueError 0.6931471805599453 1.0 ValueError 1.0986122886681096 1.0 -0.6931471805599453 -1.0 0.4054651081081644 1.0 ValueError -36.7368005696771 -1.0 0.6931471805599453 1.0 0.6931471805599454 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 ValueError 6.90875477931522 1.0 ValueError 690.7755278982137 1.0 43.66827237527655 1.0 ValueError inf 1.0 ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.log2(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
ValueError 0.0 1.0 ValueError ValueError ValueError 0.0 1.0 ValueError 1.0 1.0 ValueError -1.0 -1.0 ValueError ValueError -1.6017132519074588e-16 -1.0 3.203426503814917e-16 1.0 ValueError -1074.0 -1.0 ValueError -996.5784284662087 -1.0 ValueError 9.965784284662087 1.0 ValueError 996.5784284662087 1.0 63.0 1.0 ValueError inf 1.0 ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.pow(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
1.0 1.0 0.0 1.0 ValueError ValueError ValueError 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError 0.0 1.0 ValueError 0.0 1.0 0.0 1.0 inf 1.0 nan 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 -9.0 -1.0 -2.581174791713197e-09 -1.0 0.012345679012345678 1.0 -0.1111111111111111 -1.0 1.0 1.0 1.0 1.0 ValueError -9.0 -1.0 81.0 1.0 -729.0 -1.0 0.0 1.0 OverflowError ValueError ValueError inf 1.0 0.0 1.0 nan 1.0 1.0 -2.0 -1.0 -0.001953125 -1.0 0.25 1.0 -0.5 -1.0 1.0 1.0 1.0 1.0 ValueError -2.0 -1.0 4.0 1.0 -8.0 -1.0 0.0 1.0 OverflowError ValueError ValueError inf 1.0 0.0 1.0 nan 1.0 1.0 -1.0 -1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 ValueError -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 ValueError ValueError 1.0 1.0 1.0 1.0 nan 1.0 1.0 -0.0 -1.0 ValueError ValueError ValueError 1.0 1.0 1.0 1.0 0.0 1.0 -0.0 -1.0 0.0 1.0 -0.0 -1.0 ValueError 0.0 1.0 ValueError 0.0 1.0 0.0 1.0 inf 1.0 nan 1.0 1.0 0.0 1.0 ValueError ValueError ValueError 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError 0.0 1.0 ValueError 0.0 1.0 0.0 1.0 inf 1.0 nan 1.0 1.0 0.5 1.0 512.0 1.0 4.0 1.0 2.0 1.0 1.0 1.0 1.0 1.0 0.7071067811865476 1.0 0.5 1.0 0.25 1.0 0.125 1.0 OverflowError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 inf 1.0 nan 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 2.0 1.0 0.001953125 1.0 0.25 1.0 0.5 1.0 1.0 1.0 1.0 1.0 1.4142135623730951 1.0 2.0 1.0 4.0 1.0 8.0 1.0 0.0 1.0 OverflowError 1.0 1.0 1.0 1.0 inf 1.0 0.0 1.0 nan 1.0 1.0 3.0 1.0 5.080526342529086e-05 1.0 0.1111111111111111 1.0 0.3333333333333333 1.0 1.0 1.0 1.0 1.0 1.7320508075688772 1.0 3.0 1.0 9.0 1.0 27.0 1.0 0.0 1.0 OverflowError 1.0 1.0 1.0 1.0 inf 1.0 0.0 1.0 nan 1.0 1.0 -1e+300 -1.0 -0.0 -1.0 0.0 1.0 -1e-300 -1.0 1.0 1.0 1.0 1.0 ValueError -1e+300 -1.0 OverflowError OverflowError 0.0 1.0 OverflowError ValueError ValueError inf 1.0 0.0 1.0 nan 1.0 1.0 1e+300 1.0 0.0 1.0 0.0 1.0 1e-300 1.0 1.0 1.0 1.0 1.0 1e+150 1.0 1e+300 1.0 OverflowError OverflowError 0.0 1.0 OverflowError 1.0 1.0 1.0 1.0 inf 1.0 0.0 1.0 nan 1.0 1.0 -5e-324 -1.0 OverflowError OverflowError OverflowError 1.0 1.0 1.0 1.0 ValueError -5e-324 -1.0 0.0 1.0 -0.0 -1.0 OverflowError 0.0 1.0 ValueError ValueError 0.0 1.0 inf 1.0 nan 1.0 1.0 5e-324 1.0 OverflowError OverflowError OverflowError 1.0 1.0 1.0 1.0 2.2227587494850775e-162 1.0 5e-324 1.0 0.0 1.0 0.0 1.0 OverflowError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 inf 1.0 nan 1.0 1.0 inf 1.0 0.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 inf 1.0 inf 1.0 inf 1.0 inf 1.0 0.0 1.0 inf 1.0 0.0 1.0 inf 1.0 inf 1.0 0.0 1.0 nan 1.0 1.0 -inf -1.0 -0.0 -1.0 0.0 1.0 -0.0 -1.0 1.0 1.0 1.0 1.0 inf 1.0 -inf -1.0 inf 1.0 -inf -1.0 0.0 1.0 inf 1.0 0.0 1.0 inf 1.0 inf 1.0 0.0 1.0 nan 1.0 1.0 nan nan nan nan 1.0 1.0 1.0 1.0 nan nan nan nan nan nan nan nan nan nan nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x, y):
try:
value = m.remainder(x, y)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
for y in [False, True, -9, -2, -1, -0.0, 0.0, 0.5, 1.0, 2.0, 3.0, -1e300, 1e300, -5e-324, 5e-324, m.inf, -m.inf, m.nan]:
checked(x, y)
checked("bad", 1)
checked(1, "bad")
checked(None, 1)
checked(1, None)
return 0
Expected standard output:
ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 nan ValueError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -0.0 -1.0 -9.0 -1.0 -9.0 -1.0 -0.0 -1.0 -0.0 -1.0 -9.0 -1.0 -9.0 -1.0 nan ValueError -0.0 -1.0 -2.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 1.0 1.0 -2.0 -1.0 -2.0 -1.0 -0.0 -1.0 -0.0 -1.0 -2.0 -1.0 -2.0 -1.0 nan ValueError -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.0 -1.0 -0.0 -1.0 -1.0 -1.0 -1.0 -1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 nan ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 nan ValueError 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 ValueError ValueError 0.0 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.5 1.0 0.0 1.0 0.0 1.0 0.5 1.0 0.5 1.0 nan ValueError 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 nan ValueError 0.0 1.0 2.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 -1.0 -1.0 2.0 1.0 2.0 1.0 0.0 1.0 0.0 1.0 2.0 1.0 2.0 1.0 nan ValueError 0.0 1.0 3.0 1.0 -1.0 -1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 -1.0 -1.0 0.0 1.0 3.0 1.0 3.0 1.0 0.0 1.0 0.0 1.0 3.0 1.0 3.0 1.0 nan ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 ValueError ValueError -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -0.0 -1.0 -1e+300 -1.0 -1e+300 -1.0 nan ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 ValueError ValueError 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 1.0 1e+300 1.0 1e+300 1.0 nan ValueError -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 ValueError ValueError -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -5e-324 -1.0 -0.0 -1.0 -0.0 -1.0 -5e-324 -1.0 -5e-324 -1.0 nan ValueError 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 ValueError ValueError 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 5e-324 1.0 0.0 1.0 0.0 1.0 5e-324 1.0 5e-324 1.0 nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError ValueError nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.sin(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.8414709848078965 1.0 -0.0 -1.0 0.0 1.0 -0.8414709848078965 -1.0 0.8414709848078965 1.0 -0.9092974268256817 -1.0 0.9092974268256817 1.0 -0.479425538604203 -1.0 0.479425538604203 1.0 -0.8414709848078966 -1.0 -0.8414709848078964 -1.0 0.8414709848078964 1.0 0.8414709848078966 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -0.8268795405320025 -1.0 0.8268795405320025 1.0 0.8178819121159085 1.0 -0.8178819121159085 -1.0 0.9999303766734422 1.0 -0.9999303766734422 -1.0 ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.sinh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.1752011936438014 1.0 -0.0 -1.0 0.0 1.0 -1.1752011936438014 -1.0 1.1752011936438014 1.0 -3.626860407847019 -1.0 3.626860407847019 1.0 -0.5210953054937474 -1.0 0.5210953054937474 1.0 -1.1752011936438018 -1.0 -1.1752011936438014 -1.0 1.1752011936438014 1.0 1.1752011936438018 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 OverflowError OverflowError OverflowError OverflowError OverflowError OverflowError inf 1.0 -inf -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.sqrt(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.0 1.0 -0.0 -1.0 0.0 1.0 ValueError 1.0 1.0 ValueError 1.4142135623730951 1.0 ValueError 0.7071067811865476 1.0 ValueError ValueError 0.9999999999999999 1.0 1.0 1.0 ValueError 2.2227587494850775e-162 1.0 ValueError 1e-150 1.0 ValueError 31.622776601683793 1.0 ValueError 1e+150 1.0 3037000499.97605 1.0 ValueError inf 1.0 ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.tan(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 1.5574077246549023 1.0 -0.0 -1.0 0.0 1.0 -1.5574077246549023 -1.0 1.5574077246549023 1.0 2.185039863261519 1.0 -2.185039863261519 -1.0 -0.5463024898437905 -1.0 0.5463024898437905 1.0 -1.557407724654903 -1.0 -1.5574077246549018 -1.0 1.5574077246549018 1.0 1.557407724654903 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -1.4703241557027185 -1.0 1.4703241557027185 1.0 -1.4214488238747245 -1.0 1.4214488238747245 1.0 84.73931296875567 1.0 -84.73931296875567 -1.0 ValueError ValueError nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.tanh(x)
print(value)
if not m.isnan(value):
print(m.copysign(1, value))
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1, 1, -2, 2, -0.5, 0.5, -1.0000000000000002, -0.9999999999999999, 0.9999999999999999, 1.0000000000000002, -5e-324, 5e-324, -1e-300, 1e-300, -1000.0, 1000.0, -1e300, 1e300, 9223372036854775807, -9223372036854775808, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0.0 1.0 0.7615941559557649 1.0 -0.0 -1.0 0.0 1.0 -0.7615941559557649 -1.0 0.7615941559557649 1.0 -0.9640275800758169 -1.0 0.9640275800758169 1.0 -0.46211715726000974 -1.0 0.46211715726000974 1.0 -0.761594155955765 -1.0 -0.7615941559557649 -1.0 0.7615941559557649 1.0 0.761594155955765 1.0 -5e-324 -1.0 5e-324 1.0 -1e-300 -1.0 1e-300 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 1.0 1.0 -1.0 -1.0 1.0 1.0 -1.0 -1.0 nan TypeError TypeError TypeError TypeError
Expected exit code: 0
*import math as m
def checked(x):
try:
value = m.trunc(x)
print(value)
except ValueError:
print("ValueError")
except OverflowError:
print("OverflowError")
except TypeError:
print("TypeError")
except ZeroDivisionError:
print("ZeroDivisionError")
def main():
for x in [False, True, -0.0, 0.0, -1.5, 1.5, -0.1, 0.1, -5e-324, 5e-324, 9007199254740993, -9007199254740993, 9223372036854775807, -9223372036854775808, 9223372036854774784.0, -9223372036854775808.0, m.inf, -m.inf, m.nan, "bad", None, [], {}]:
checked(x)
return 0
Expected standard output:
0 1 0 0 -1 1 0 0 0 0 9007199254740993 -9007199254740993 9223372036854775807 -9223372036854775808 9223372036854774784 -9223372036854775808 OverflowError OverflowError ValueError TypeError TypeError TypeError TypeError
Expected exit code: 0
e = 0x1.5bf0a8b145769p+1
Binary64 approximation of the base of natural logarithms.
inf = inf
Positive infinity; negate it to express negative infinity.
nan = nan
A quiet NaN value; classify it using isnan, not equality.
pi = 0x1.921fb54442d18p+1
Binary64 approximation of the circle constant pi.
tau = 0x1.921fb54442d18p+2
Binary64 approximation of two times pi.