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Creation Functions for 2D Arrays | NumPy Basics
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Creation Functions for 2D Arrays

Similarly to 1D arrays, NumPy has creation functions for 2D arrays. We will cover the most common one, the eye() function.

eye()

The numpy.eye() function creates a matrix in the format of a 2D array where the elements with equal row and column indices are 1, while all other elements are 0.

The two most important parameters are N and M, which specify the number of rows and columns respectively. The M parameter is optional, so you can specify only N to create a square NxN matrix.

import numpy as np
# Creating a 2x2 identity matrix
identity_matrix = np.eye(2)
print(f'2x2 identity matrix:\n{identity_matrix}')
# Creating a 4x3 matrix with np.eye()
rectangular_matrix = np.eye(4, 3, dtype=np.int8)
print(f'4x3 matrix:\n{rectangular_matrix}')
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import numpy as np # Creating a 2x2 identity matrix identity_matrix = np.eye(2) print(f'2x2 identity matrix:\n{identity_matrix}') # Creating a 4x3 matrix with np.eye() rectangular_matrix = np.eye(4, 3, dtype=np.int8) print(f'4x3 matrix:\n{rectangular_matrix}')
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In our example, we created an identity matrix by specifying only the N parameter and a rectangular matrix by specifying both N and M. We also set the dtype to np.int8 for the rectangular matrix, which can be useful when working with only integers (np.float64 is the default value for dtype).

The resulting 2D arrays look as follows:

Regarding applications, the eye() function is primarily used to create identity matrices for specific linear algebra operations and to initialize matrices in machine learning algorithms.

Tarea
test

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  1. Use the correct function for matrix to create a matrix where the elements with equal row index and column index are 1, while all other elements are 0.
  2. Specify the first two arguments so that array_1 is a 5x2 matrix.
  3. Set the data type of array_1 elements to np.int8.

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Sección 1. Capítulo 5
import numpy as np
# Create 5x2 array with ones for elements with equal row index and column index
matrix = ___.___(___, ___, ___=___)
print(matrix)
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