8000 Fixed implementation against CPython 3.12.9 Lib/test/test_math.py tests · RustPython/RustPython@60805fb · GitHub
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Commit 60805fb

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hbinahbina
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Fixed implementation against CPython 3.12.9 Lib/test/test_math.py tests
Signed-off-by: Hanif Ariffin <hanif.ariffin.4326@gmail.com>
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‎Lib/test/ieee754.txt

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======================================
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Python IEEE 754 floating point support
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======================================
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>>> from sys import float_info as FI
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>>> from math import *
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>>> PI = pi
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>>> E = e
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You must never compare two floats with == because you are not going to get
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what you expect. We treat two floats as equal if the difference between them
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is small than epsilon.
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>>> EPS = 1 8000 E-15
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>>> def equal(x, y):
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... """Almost equal helper for floats"""
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... return abs(x - y) < EPS
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NaNs and INFs
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=============
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In Python 2.6 and newer NaNs (not a number) and infinity can be constructed
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from the strings 'inf' and 'nan'.
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>>> INF = float('inf')
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>>> NINF = float('-inf')
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>>> NAN = float('nan')
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>>> INF
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inf
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>>> NINF
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-inf
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>>> NAN
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nan
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The math module's ``isnan`` and ``isinf`` functions can be used to detect INF
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and NAN:
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>>> isinf(INF), isinf(NINF), isnan(NAN)
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(True, True, True)
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>>> INF == -NINF
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True
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Infinity
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--------
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Ambiguous operations like ``0 * inf`` or ``inf - inf`` result in NaN.
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>>> INF * 0
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nan
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>>> INF - INF
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nan
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>>> INF / INF
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nan
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However unambiguous operations with inf return inf:
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>>> INF * INF
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inf
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>>> 1.5 * INF
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inf
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>>> 0.5 * INF
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inf
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>>> INF / 1000
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inf
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Not a Number
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------------
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NaNs are never equal to another number, even itself
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>>> NAN == NAN
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False
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>>> NAN < 0
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False
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>>> NAN >= 0
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False
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All operations involving a NaN return a NaN except for nan**0 and 1**nan.
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>>> 1 + NAN
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nan
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>>> 1 * NAN
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nan
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>>> 0 * NAN
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nan
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>>> 1 ** NAN
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1.0
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>>> NAN ** 0
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1.0
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>>> 0 ** NAN
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nan
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>>> (1.0 + FI.epsilon) * NAN
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nan
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Misc Functions
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==============
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The power of 1 raised to x is always 1.0, even for special values like 0,
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infinity and NaN.
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>>> pow(1, 0)
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1.0
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>>> pow(1, INF)
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1.0
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>>> pow(1, -INF)
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1.0
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>>> pow(1, NAN)
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1.0
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The power of 0 raised to x is defined as 0, if x is positive. Negative
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finite values are a domain error or zero division error and NaN result in a
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silent NaN.
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>>> pow(0, 0)
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1.0
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>>> pow(0, INF)
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0.0
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>>> pow(0, -INF)
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inf
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>>> 0 ** -1
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Traceback (most recent call last):
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...
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ZeroDivisionError: 0.0 cannot be raised to a negative power
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>>> pow(0, NAN)
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nan
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Trigonometric Functions
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=======================
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>>> sin(INF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> sin(NINF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> sin(NAN)
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nan
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>>> cos(INF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> cos(NINF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> cos(NAN)
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nan
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>>> tan(INF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> tan(NINF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> tan(NAN)
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nan
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Neither pi nor tan are exact, but you can assume that tan(pi/2) is a large value
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and tan(pi) is a very small value:
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>>> tan(PI/2) > 1E10
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True
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>>> -tan(-PI/2) > 1E10
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True
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>>> tan(PI) < 1E-15
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True
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>>> asin(NAN), acos(NAN), atan(NAN)
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(nan, nan, nan)
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>>> asin(INF), asin(NINF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> acos(INF), acos(NINF)
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Traceback (most recent call last):
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...
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ValueError: math domain error
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>>> equal(atan(INF), PI/2), equal(atan(NINF), -PI/2)
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(True, True)
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Hyberbolic Functions
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====================
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