NumPy offers a variety of functions and tools to work with arrays and matrices, making it an excellent choice for data manipulation and analysis. In this article, we will learn how to build a new vector with ‘n’ consecutive zeros interleaved between each value using NumPy.
- In the following examples, we will suppose that we need 3 zeros between each element in our array.
1. Using “np.insert()”:
Here, num_zeros specify the number of zeros to be inserted. The np.insert() function is used to insert the zeros between each value of the input vector. The np.repeat() function repeats each index of the input vector num_zeros times to insert num_zeros consecutive zeros after each index. The np.arange(1, len(input_vec)) function creates an array of indices starting from 1 to len(input_vec)-1, which represent the positions where zeros are to be inserted. Finally, the 0 argument in the np.insert() function specifies the value to be inserted, which is zero in this case.
2. Using “np.kron()”:
The code uses NumPy library to create a new array new_vector by repeating the original_vector 4 times and multiplying it element-wise with a pattern array. The pattern array is created by using np.ones() and np.zeros() to create arrays of 1s and 0s, and then using np.kron() to concatenate them into an alternating pattern of 1s and 0s. The resulting new vector with 3 consecutive zeros interleaved between each value is stored in the new_vector variable and printed using print(new_vector).