Numeric and Mathematical Modules

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Numeric and Mathematical Modules

2023-11-18 09:12| 来源: 网络整理| 查看: 265

Numeric and Mathematical Modules¶

The modules described in this chapter provide numeric and math-related functions and data types. The numbers module defines an abstract hierarchy of numeric types. The math and cmath modules contain various mathematical functions for floating-point and complex numbers. The decimal module supports exact representations of decimal numbers, using arbitrary precision arithmetic.

The following modules are documented in this chapter:

numbers — Numeric abstract base classes The numeric tower Notes for type implementors Adding More Numeric ABCs Implementing the arithmetic operations math — Mathematical functions Number-theoretic and representation functions Power and logarithmic functions Trigonometric functions Angular conversion Hyperbolic functions Special functions Constants cmath — Mathematical functions for complex numbers Conversions to and from polar coordinates Power and logarithmic functions Trigonometric functions Hyperbolic functions Classification functions Constants decimal — Decimal fixed point and floating point arithmetic Quick-start Tutorial Decimal objects Logical operands Context objects Constants Rounding modes Signals Floating Point Notes Mitigating round-off error with increased precision Special values Working with threads Recipes Decimal FAQ fractions — Rational numbers random — Generate pseudo-random numbers Bookkeeping functions Functions for bytes Functions for integers Functions for sequences Discrete distributions Real-valued distributions Alternative Generator Notes on Reproducibility Examples Recipes statistics — Mathematical statistics functions Averages and measures of central location Measures of spread Statistics for relations between two inputs Function details Exceptions NormalDist objects NormalDist Examples and Recipes Classic probability problems Monte Carlo inputs for simulations Approximating binomial distributions Naive bayesian classifier Kernel density estimation


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