https://github.com/afcms/math_algorithms

https://github.com/afcms/math_algorithms

math python

Last synced: 29 days ago
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• Host: GitHub
• URL: https://github.com/afcms/math_algorithms
• Owner: AFCMS
• Created: 2022-12-22T20:13:01.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2023-11-21T13:22:24.000Z (about 1 year ago)
• Last Synced: 2024-11-01T09:42:16.006Z (3 months ago)
• Topics: math, python
• Language: Python
• Homepage:
• Size: 403 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Math Algorithms

Some algorithms I made to understand maths better.

| Name                          | Status | Tests? |

|-------------------------------|--------|--------|

| [Binomial Law](#binomial-law) | Done   | ✅      |

| [Matrix](#matrix)             | WIP    | ✅      |

| Sequences                     | WIP    | ❌      |

| Vectors                       | TODO   | ❌      |

## Binomial law

```python

from binomial_law import *

# Binomial law of parameters n = 10 and p = 0.2

X = Binomial(10, 0.2)

print(f"X -> {X}")

print(f"Expectation of X: {X.expected}")

print(f"Variance of X:  {X.variance}")

print(f"Sigma of X:  {X.sigma}")

print(f"P(X=8)  = {X == 8}")

print(f"P(X>8)  = {X > 8}")

print(f"P(X>=8) = {X >= 8}")

print(f"P(X<8)  = {X < 8}")

print(f"P(X<=8) = {X <= 8}")

```

Also provide function to visualize a law using `matplotlib.pyplot`:

```python

from binomial_law import *

X = Binomial(10, 0.2)

show_graph(X)

```

![PyCharm Binomial Law](images/binomial_law.png)

# Matrix

```python

from matrix import Matrix

A = Matrix([

	[1, 2, 3],

	[0, 4, -1],

])

assert A.size == (2, 3)

assert A.is_square == False

assert A.is_line == False

assert A.is_column == False

B = Matrix([

	[1, 0, 0],

	[0, 2, 0],

	[0, 0, 0],

])

assert B.size == (3, 3)

assert B.is_square == True

assert B.is_line == False

assert B.is_column == False

assert A * B == Matrix([

	[1, 4, 0],

	[0, 8, 0]

])

assert -A == Matrix([

	[-1, -2, -3],

	[0, -4, 1],

])

I2 = Matrix.identity(2)

O2 = Matrix.null(2)

```