Christian Heimes | 6f34109 | 2008-04-18 23:13:07 +0000 | [diff] [blame] | 1 | ====================================== |
| 2 | Python IEEE 754 floating point support |
| 3 | ====================================== |
| 4 | |
| 5 | >>> from sys import float_info as FI |
| 6 | >>> from math import * |
| 7 | >>> PI = pi |
| 8 | >>> E = e |
| 9 | |
| 10 | You must never compare two floats with == because you are not going to get |
| 11 | what you expect. We treat two floats as equal if the difference between them |
| 12 | is small than epsilon. |
| 13 | >>> EPS = 1E-15 |
| 14 | >>> def equal(x, y): |
| 15 | ... """Almost equal helper for floats""" |
| 16 | ... return abs(x - y) < EPS |
| 17 | |
| 18 | |
| 19 | NaNs and INFs |
| 20 | ============= |
| 21 | |
| 22 | In Python 2.6 and newer NaNs (not a number) and infinity can be constructed |
| 23 | from the strings 'inf' and 'nan'. |
| 24 | |
| 25 | >>> INF = float('inf') |
| 26 | >>> NINF = float('-inf') |
| 27 | >>> NAN = float('nan') |
| 28 | |
| 29 | >>> INF |
| 30 | inf |
| 31 | >>> NINF |
| 32 | -inf |
| 33 | >>> NAN |
| 34 | nan |
| 35 | |
| 36 | The math module's ``isnan`` and ``isinf`` functions can be used to detect INF |
| 37 | and NAN: |
| 38 | >>> isinf(INF), isinf(NINF), isnan(NAN) |
| 39 | (True, True, True) |
| 40 | >>> INF == -NINF |
| 41 | True |
| 42 | |
| 43 | Infinity |
| 44 | -------- |
| 45 | |
| 46 | Ambiguous operations like ``0 * inf`` or ``inf - inf`` result in NaN. |
| 47 | >>> INF * 0 |
| 48 | nan |
| 49 | >>> INF - INF |
| 50 | nan |
| 51 | >>> INF / INF |
| 52 | nan |
| 53 | |
| 54 | However unambigous operations with inf return inf: |
| 55 | >>> INF * INF |
| 56 | inf |
| 57 | >>> 1.5 * INF |
| 58 | inf |
| 59 | >>> 0.5 * INF |
| 60 | inf |
| 61 | >>> INF / 1000 |
| 62 | inf |
| 63 | |
| 64 | Not a Number |
| 65 | ------------ |
| 66 | |
| 67 | NaNs are never equal to another number, even itself |
| 68 | >>> NAN == NAN |
| 69 | False |
| 70 | >>> NAN < 0 |
| 71 | False |
| 72 | >>> NAN >= 0 |
| 73 | False |
| 74 | |
Mark Dickinson | 99d652e | 2009-12-30 12:12:23 +0000 | [diff] [blame] | 75 | All operations involving a NaN return a NaN except for nan**0 and 1**nan. |
Christian Heimes | 6f34109 | 2008-04-18 23:13:07 +0000 | [diff] [blame] | 76 | >>> 1 + NAN |
| 77 | nan |
| 78 | >>> 1 * NAN |
| 79 | nan |
| 80 | >>> 0 * NAN |
| 81 | nan |
| 82 | >>> 1 ** NAN |
| 83 | 1.0 |
Mark Dickinson | 99d652e | 2009-12-30 12:12:23 +0000 | [diff] [blame] | 84 | >>> NAN ** 0 |
| 85 | 1.0 |
Christian Heimes | 6f34109 | 2008-04-18 23:13:07 +0000 | [diff] [blame] | 86 | >>> 0 ** NAN |
Mark Dickinson | 99d652e | 2009-12-30 12:12:23 +0000 | [diff] [blame] | 87 | nan |
Christian Heimes | 6f34109 | 2008-04-18 23:13:07 +0000 | [diff] [blame] | 88 | >>> (1.0 + FI.epsilon) * NAN |
| 89 | nan |
| 90 | |
| 91 | Misc Functions |
| 92 | ============== |
| 93 | |
| 94 | The power of 1 raised to x is always 1.0, even for special values like 0, |
| 95 | infinity and NaN. |
| 96 | |
| 97 | >>> pow(1, 0) |
| 98 | 1.0 |
| 99 | >>> pow(1, INF) |
| 100 | 1.0 |
| 101 | >>> pow(1, -INF) |
| 102 | 1.0 |
| 103 | >>> pow(1, NAN) |
| 104 | 1.0 |
| 105 | |
| 106 | The power of 0 raised to x is defined as 0, if x is positive. Negative |
| 107 | values are a domain error or zero division error and NaN result in a |
| 108 | silent NaN. |
| 109 | |
| 110 | >>> pow(0, 0) |
| 111 | 1.0 |
| 112 | >>> pow(0, INF) |
| 113 | 0.0 |
| 114 | >>> pow(0, -INF) |
| 115 | Traceback (most recent call last): |
| 116 | ... |
| 117 | ValueError: math domain error |
| 118 | >>> 0 ** -1 |
| 119 | Traceback (most recent call last): |
| 120 | ... |
| 121 | ZeroDivisionError: 0.0 cannot be raised to a negative power |
| 122 | >>> pow(0, NAN) |
| 123 | nan |
| 124 | |
| 125 | |
| 126 | Trigonometric Functions |
| 127 | ======================= |
| 128 | |
| 129 | >>> sin(INF) |
| 130 | Traceback (most recent call last): |
| 131 | ... |
| 132 | ValueError: math domain error |
| 133 | >>> sin(NINF) |
| 134 | Traceback (most recent call last): |
| 135 | ... |
| 136 | ValueError: math domain error |
| 137 | >>> sin(NAN) |
| 138 | nan |
| 139 | >>> cos(INF) |
| 140 | Traceback (most recent call last): |
| 141 | ... |
| 142 | ValueError: math domain error |
| 143 | >>> cos(NINF) |
| 144 | Traceback (most recent call last): |
| 145 | ... |
| 146 | ValueError: math domain error |
| 147 | >>> cos(NAN) |
| 148 | nan |
| 149 | >>> tan(INF) |
| 150 | Traceback (most recent call last): |
| 151 | ... |
| 152 | ValueError: math domain error |
| 153 | >>> tan(NINF) |
| 154 | Traceback (most recent call last): |
| 155 | ... |
| 156 | ValueError: math domain error |
| 157 | >>> tan(NAN) |
| 158 | nan |
| 159 | |
| 160 | Neither pi nor tan are exact, but you can assume that tan(pi/2) is a large value |
| 161 | and tan(pi) is a very small value: |
| 162 | >>> tan(PI/2) > 1E10 |
| 163 | True |
| 164 | >>> -tan(-PI/2) > 1E10 |
| 165 | True |
| 166 | >>> tan(PI) < 1E-15 |
| 167 | True |
| 168 | |
| 169 | >>> asin(NAN), acos(NAN), atan(NAN) |
| 170 | (nan, nan, nan) |
| 171 | >>> asin(INF), asin(NINF) |
| 172 | Traceback (most recent call last): |
| 173 | ... |
| 174 | ValueError: math domain error |
| 175 | >>> acos(INF), acos(NINF) |
| 176 | Traceback (most recent call last): |
| 177 | ... |
| 178 | ValueError: math domain error |
| 179 | >>> equal(atan(INF), PI/2), equal(atan(NINF), -PI/2) |
| 180 | (True, True) |
| 181 | |
| 182 | |
| 183 | Hyberbolic Functions |
| 184 | ==================== |
| 185 | |