NumPy is a popular Python library used for numerical computations. It provides various mathematical functions and tools for manipulating arrays, which are multi-dimensional data structures that can hold homogeneous data. To add ‘n’ to each element indexed by a second vector using NumPy, we can use the following methods:
1. Using “np.add.at()”:
Here, you first import the NumPy library and then create two random arrays Z and I. Here, 'n' is the number that you want to increment in the first vector’s element, whose index is present in the second vector. Then, you can use the np.add.at() function to add the count of each index in I to the corresponding element in Z. This function allows you to specify the indices and values to add and handles duplicates correctly.
2. Using a “for loop”:
Here, you first import the NumPy library and then create two random arrays Z and I. Here, 'n' is the number that you want to increment in the first vector’s element, whose index is present in the second vector. You can loop over the indices in I and add 1 to the corresponding element in Z. This method is less efficient than using np.add.at(), but is more explicit and easier to understand.