线性方程组 python

Prerequisites:

先决条件：

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，我们将学习如何使用线性代数在Python中表示线性方程。 例如，我们正在考虑具有3个变量( x，y，z 和t )的方程。

3x + 4y - 7z + 12t = 46    2x + 7y - 13z + 3t = 65    34x + 4y - 4z + 34t = 78

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

上式的线性代数形式如下：

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

Application:

应用：

1. Machine Learning

   机器学习

2. Calculus

   结石

3. Linear Programming

   线性规划

4. Physics and Kinetic Studies

   物理与动力学研究

用于表示线性方程组的Python代码 (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 VectorA = 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:

输出：

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

翻译自:

线性方程组 python