Use numpy to

perform matrix multiplication of two matrices A and B:

import numpy as np

A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])

C = np.dot(A, B)

print(C)

Output:

[[19 22]
 [43 50]]

Note that the `dot` function in numpy is used for matrix multiplication. Alternatively, you can also use the `@` operator:

C = A @ B

print(C)

Output is the same as above:

[[19 22]
 [43 50]]

相关问题

how to use numpy with list as dtype

To use a list as the data type in NumPy, you can create a NumPy array with the `object` data type and then fill it with lists.

Here is an example:

import numpy as np

# Create a NumPy array with the object data type
arr = np.empty(shape=(3,), dtype=object)

# Fill the array with lists
arr[0] = [1, 2, 3]
arr[1] = [4, 5, 6]
arr[2] = [7, 8, 9]

# Print the NumPy array
print(arr)

Output:

[array([1, 2, 3]) array([4, 5, 6]) array([7, 8, 9])]

In this example, we create a NumPy array with the `object` data type and a shape of `(3,)`. We then fill the array with lists and print the array.

numpy to list

To convert a NumPy array to a Python list, you can use the `tolist()` method. Here's an example:

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
list_arr = arr.tolist()

print(list_arr)  # Output: [1, 2, 3, 4, 5]

In this example, we create a NumPy array `arr` and then convert it to a list using the `tolist()` method. The resulting list is stored in the variable `list_arr`.