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