Python Numerical Computing

Introduction

In this lab, we will dive into the world of numerical computing using Python. Imagine a scenario in the dinosaur age where a primitive earth wizard is trying to predict the movement of celestial bodies using basic numerical calculations. The wizard's goal is to understand the concepts of numerical computing and apply them to solve simple mathematical problems.

Skills Graph

Setting Up the Python Environment

In this step, we will set up a Python environment for numerical computing.

Let's write a simple Python code snippet to perform basic numerical computations. Add the following code to /home/labex/project/numerical_computing.py:

## numerical_computing.py
## Performing basic numerical computations

## Addition
result_addition = 3 + 5
print("Result of addition:", result_addition)

## Subtraction
result_subtraction = 10 - 3
print("Result of subtraction:", result_subtraction)

Run the script:

python numerical_computing.py

The information below should be displayed on your terminal:

Result of addition: 8
Result of subtraction: 7

Working with NumPy Library

In this step, we will introduce the NumPy library for numerical computing. We will work on arrays, perform basic operations, and calculate statistical values.

Now, let's add code to /home/labex/project/numpy_operations.py for performing basic numerical computations using the NumPy library.

## numpy_operations.py
## Working with NumPy Library

import numpy as np

## Creating arrays
array1 = np.array([1, 2, 3, 4, 5])
array2 = np.array([6, 7, 8, 9, 10])

## Performing array operations
result_addition = array1 + array2
print("Result of addition:", result_addition)

## Calculating mean
mean_value = np.mean(array1)
print("Mean value of array1:", mean_value)

Run the script:

python numpy_operations.py

The information below should be displayed on your terminal:

Result of addition: [ 7  9 11 13 15]
Mean value of array1: 3.0

Summary

In this lab, we have explored the basics of numerical computing using Python. We set up a Python environment, performed basic numerical computations, and worked with the NumPy library to manipulate arrays and calculate statistical values. This lab provides a solid foundation for understanding numerical computing concepts and their application in Python.