線性方程組 python

Prerequisites:

先決條件：

• Defining a Vectors

  定義向量

• Defining a Matrix

  定義矩陣

In this article, we are going to learn how to represent a linear equation in Python using Linear Algebra. For example we are considering an equation with 3 variables (x,y,z and t).

在本文中，我們將學習如何使用線性代數在Python中表示線性方程。 例如，我們正在考慮具有3個變量( x，y，z 和t )的方程。

3x + 4y - 7z + 12t = 462x + 7y - 13z + 3t = 6534x + 4y - 4z + 34t = 78

The above equation has a form as below in linear Algebra:

上式的線性代數形式如下：

Ax = b, x = (x y z t)

Application:

應用：

Machine Learning

機器學習

Calculus

結石

Linear Programming

線性規劃

Physics and Kinetic Studies

物理與動力學研究

用于表示線性方程組的Python代碼 (Python code for Representation of a system of linear equation)

# Linear Algebra Learning Sequence # Representation of a System of Linear Equationimport numpy as np# Use of np.array() to define an Vector A = np.array([[3, 4, -7, 12], [2, 7, -13, 3], [34, 4, -4, 34]]) b = np.array([46, 65, 78]) print("The Matrix A : \n",A)x = np.array(['x', 'y', 'z', 't']) print("\nThe Vector x : ",x) print("\nThe Vector b : ",b)print("\n---Now the equations is represented in form of vector: Ax = b---") print("This is just a python intrepetation of understanding a linear equation")

Output:

輸出：

The Matrix A : [[ 3 4 -7 12][ 2 7 -13 3][ 34 4 -4 34]]The Vector x : ['x' 'y' 'z' 't']The Vector b : [46 65 78]---Now the equations is represented in form of vector: Ax = b--- This is just a python intrepetation of understanding a linear equation

翻譯自: https://www.includehelp.com/python/representation-of-a-system-of-linear-equation.aspx

線性方程組 python

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