This article mainly introduces pythonr's knowledge about the digital processing module (math). For more information, see section 1. math.

The Code is as follows:

>>> Import math

>>> Dir (math) # You can view the list of all function names.

>>> Help (math) # view the definition and function 0 prototype

2. Common functions

The Code is as follows:

Ceil (x) Top

Floor (x) Base fetch

Fabs (x) returns the absolute value.

Factorial (x) factorial

Hypot (x, y) sqrt (x * x + y * y)

Power y of pow (x, y) x

Sqrt (x) Square

Log (x)

Log10 (x)

Trunc (x) truncation integer

Isnan (x) determines whether NaN (not a number)

Degree (x) radians Rotation Angle

Radians (x) angle to radian

In addition, this module defines two constants:

The Code is as follows:

E = 2.718281828459045

Pi = 1, 3.141592653589793

Random

1. Introduction

Random is used to generate random numbers. We can use it to randomly generate numbers or select strings.

The Code is as follows:

Import random

2. Common functions

Random. random ()

Used to generate a random floating point number: range [0.0, 1.0)

The Code is as follows:

>>> Import random

>>> Random. random ()

0.999410896951364

Random. uniform (a, B)

Generates a random floating point number in the specified range. a and B are upper and lower limits.

As long as! = B, a floating point number between the two is generated. If a = B, the generated floating point number is

The Code is as follows:

>>> Random. uniform (10, 20)

13.224754825064881

>>> Random. uniform (20, 10)

14.104410713376437

>>> Random. uniform (10, 10)

10.0

Random. randint (a, B)

Generates an integer in the specified range. a is the lower limit, B is the upper limit, and a <= n <= B;

If a = B, n = a. If a> B, an error is returned.

The Code is as follows:

>>> Random. uniform (10, 10)

10.0

>>> Random. randint (10, 20)

15

>>> Random. randint (10, 10)

10

>>> Random. randint (20, 10)

Traceback (most recent call last ):

......

ValueError: empty range for randrange () (20, 11,-9)

Random. randrange ([start], stop, [, step])

Obtains a random number from a set that increments by the specified base number within the specified range. The default value of the base number is 1.

The Code is as follows:

>>> Random. randrange (10,100, 5)

95

>>> Random. randrange (10,100, 5)

45

Random. choice (sequence)

Obtain a random element from the sequence. The sequence parameter indicates an ordered type. It is not a specific type. It generally refers to list, tuple, string, and so on.

The Code is as follows:

>>> Random. choice ([1, 2, 3, 4])

1

>>> Random. choice ([1, 2, 3, 4])

3

>>> Random. choice ('hello ')

'E'

Random. shuffle (x [, random])

Used to disrupt elements in a list

The Code is as follows:

>>> A = [1, 2, 3, 4, 5]

>>> Random. shuffle ()

>>>

[4, 5, 2, 1, 3]

>>> Random. shuffle ()

>>>

[3, 2, 5, 1, 4]

Random. sample (sequence, k)

Returns k elements from a specified sequence as a segment. The sample function does not modify the original sequence.

The Code is as follows:

>>> A = [1, 2, 3, 4, 5]

>>> Random. sample (a, 3)

[1, 4, 5]

>>> Random. sample (a, 3)

[1, 2, 5]

>>>

[1, 2, 3, 4, 5]

Decimal

1. Introduction

By default, floating point mathematics lacks accuracy.

The decimal module provides a Decimal data type for floating point calculation. Compared with the built-in binary floating point number, float is helpful.

Financial applications and other scenarios that require precise decimal expression,

Control precision,

Control rounding to adapt to legal or regulatory requirements,

Make sure that the decimal digit is accurate or that the calculation result is consistent with the manual calculation result.

Decimal reproduce the manual mathematical operation, which ensures that the binary floating point cannot accurately preserve the data accuracy. High Precision enables Decimal to execute modulo operations and equivalent tests that are not supported by binary floating point numbers.

2. Use

The Code is as follows:

>>> From decimal import Decimal

>>> Decimal ('0. 1')/Decimal ('0. 3 ')

Decimal ('0. 3333333333333333333333333333 ')

>>> From decimal import getcontext

>>> Getcontext (). prec = 4 # set global precision

>>> Decimal ('0. 1')/Decimal ('0. 3 ')

Decimal ('0. 3333 ')

Fractions

Score type

Structure

The Code is as follows:

>>> From fractions import Fraction

>>> Fraction (16,-10) # denominator

Fraction (-8, 5)

>>> Fraction (123) # molecule

Fraction (123, 1)

>>> Fraction ('123') # string score

Fraction (3, 7)

>>> Fraction ('-. 100') # string floating point number

Fraction (-1, 8)

>>> Fraction (2.25) # Floating Point Number

Fraction (9, 4)

>>> From decimal import Decimal

>>> Fraction (Decimal ('1. 1') # Decimal

Fraction (11, 10)

Computing

The Code is as follows:

>>> From fractions import Fraction

>>> A = Fraction (1, 2)

>>>

Fraction (1, 2)

>>> B = Fraction ('20140901 ')

>>> B

Fraction (1, 3)

>>> A + B

Fraction (5, 6)

>>> A-B

Fraction (1, 6)