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Build a block matrix in Numpy
To build a block of matrix, use the numpy.block() method in Python Numpy. Blocks in the innermost lists are concatenated along the last dimension (-1), then these are concatenated along the secondlast dimension (-2), and so on until the outermost list is reached.
Blocks can be of any dimension, but will not be broadcasted using the normal rules. Instead, leading axes of size 1 are inserted, to make block.ndim the same for all blocks. This is primarily useful for working with scalars, and means that code like np.block([v, 1]) is valid, where v.ndim == 1.
Steps
At first, import the required library −
import numpy as np
Creating two numpy arrays using the array() method. We have inserted elements of int type −
arr1 = np.eye(2) * 2 arr2 = np.eye(3) * 2
Display the arrays −
print("Array 1...
", arr1)
print("
Array 2...
", arr2)Get the type of the arrays −
print("
Our Array 1 type...
", arr1.dtype)
print("
Our Array 2 type...
", arr2.dtype)Get the dimensions of the Arrays −
print("
Our Array 1 Dimensions...
",arr1.ndim)
print("
Our Array 2 Dimensions...
",arr2.ndim)Get the shape of the Arrays −
print("
Our Array 1 Shape...
",arr1.shape)
print("
Our Array 2 Shape...
",arr2.shape)To build a block of matrix, use the numpy.block() method in Python Numpy −
print("
Result...
",np.block([[arr1,np.zeros((2, 3))], [np.ones((3, 2)), arr2]]))Example
import numpy as np
# Creating two numpy arrays using the array() method
# We have inserted elements of int type
arr1 = np.eye(2) * 2
arr2 = np.eye(3) * 2
# Display the arrays
print("Array 1...
", arr1)
print("
Array 2...
", arr2)
# Get the type of the arrays
print("
Our Array 1 type...
", arr1.dtype)
print("
Our Array 2 type...
", arr2.dtype)
# Get the dimensions of the Arrays
print("
Our Array 1 Dimensions...
",arr1.ndim)
print("
Our Array 2 Dimensions...
",arr2.ndim)
# Get the shape of the Arrays
print("
Our Array 1 Shape...
",arr1.shape)
print("
Our Array 2 Shape...
",arr2.shape)
# To build a block of matrix, use the numpy.block() method in Python Numpy
print("
Result...
",np.block([[arr1,np.zeros((2, 3))], [np.ones((3, 2)), arr2]]))Output
Array 1... [[2. 0.] [0. 2.]] Array 2... [[2. 0. 0.] [0. 2. 0.] [0. 0. 2.]] Our Array 1 type... float64 Our Array 2 type... float64 Our Array 1 Dimensions... 2 Our Array 2 Dimensions... 2 Our Array 1 Shape... (2, 2) Our Array 2 Shape... (3, 3) Result... [[2. 0. 0. 0. 0.] [0. 2. 0. 0. 0.] [1. 1. 2. 0. 0.] [1. 1. 0. 2. 0.] [1. 1. 0. 0. 2.]]
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