Linear algebra on Python — вектора, матрицы, разложения
Project description
Algebrix
Algebrix is a simple and powerful library for working with vectors and matrices. Supports basic linear algebra operations, including:
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Addition, subtraction, scalar and matrix multiplication
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Normalization of vectors, calculation of angle, projections
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Transpose, inverse matrix, reshape
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And much more
Installing
pip install algebrix
Usage examples
from algebrix import Matrix, Vector
# Векторы
v1 = Vector([1, 2, 3])
v2 = Vector([4, 5, 6])
print(v1 + v2) # Vector([5, 7, 9])
print(v1.dot(v2)) # 32
print(v1.norm()) # 3.741...
print(v1.project_onto(v2)) # Проекция v1 на v2
# Матрицы
m1 = Matrix([[1, 2], [3, 4]])
m2 = Matrix([[5, 6], [7, 8]])
print(m1 + m2) # Matrix([[6, 8], [10, 12]])
print(m1 * m2) # Matrix([[19, 22], [43, 50]])
print(m1.T()) # Matrix([[1, 3], [2, 4]])
print(m1.inverse()) # Matrix([[-2.0, 1.0], [1.5, -0.5]])
🧠 Features
🟦 Vector Class
Implements:
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add, sub, mul, rmul
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dot(other): dot product
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norm(): Euclidean norm
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normalize(): unit vector
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project_onto(other): vector projection
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angle_with(other): angle between vectors (in radians)
🟩 Matrix Class
Implements:
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add, sub, mul, rmul
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T(): transpose
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inverse(): matrix inverse
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shape(): returns (rows, cols)
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reshape((new_rows, new_cols)): reshapes the matrix
🛠️ Requirements
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Python 3.10+
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Only depends on the built-in math module (no third-party dependencies)
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