data_transform_lib_turing 1.1

3 functions for data transformation

Data Transformation Library

Description

The Data Transformation Library is a Python package designed for performing various matrix operations. This package includes functions for matrix transposition, sliding window generation on 1D arrays, and applying 2D convolution on matrices.

Installation

To install the Data Transformation Library, you will need Python 3.8 or later. The package can be installed via pip directly from PyPI:

pip install data_transformation_library

Usage

Here is how you can use the functions in the Data Transformation Library:

Transpose a 2D matrix

from data_transformation_library import transpose2d

matrix = [
    [1, 2],
    [3, 4]
]
transposed = transpose2d(matrix)
print(transposed)

Create a sliding window from a 1D array

from data_transformation_library import window1d
import numpy as np

input_array = np.array([1, 2, 3, 4, 5])
windows = window1d(input_array, size=2, shift=1, stride=1)
print(windows)

Apply a 2D convolution to a matrix

from data_transformation_library import convolution2d
import numpy as np

input_matrix = np.array([
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
])
kernel = np.array([
    [1, 0],
    [0, -1]
])

convol_result = convolution2d(input_matrix, kernel)
print(convol_result)