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# Apply accumulate for a multi-dimensional array along axis 1 in Numpy

To Accumulate the result of applying the operator to all elements, use the **numpy.accumulate()** method in Python Numpy. For a multi-dimensional array, accumulate is applied along only one axis. We will apply along axis 1.

The **numpy.ufunc** has functions that operate element by element on whole arrays. The ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility. A universal function (or ufunc for short) is a function that operates on ndarrays in an element-by-element fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a“vectorized” wrapper for a function that takes a fixed number of specific inputs and produces a fixed number of specific outputs.

## Steps

At first, import the required library −

import numpy as np

Create a 2d array. The numpy.eye() returns a 2-D array with 1’s as the diagonal and 0’s elsewhere −

arr = np.eye(3)

Display the array −

print("Array...

", arr)

Get the type of the array −

print("

Our Array type...

", arr.dtype)

Get the dimensions of the Array −

print("

Our Array Dimensions...

",arr.ndim)

To Accumulate the result of applying the operator to all elements, use the numpy.accumulate() method in Python Numpy. For a multi-dimensional array, accumulate is applied along only one axis −

Add accumulate: Accumulate along axis 1 (columns) −

print("

Add accumulate...

",np.add.accumulate(arr, 1))

Multiply accumulate −

print("

Multiply accumulate...

",np.multiply.accumulate(arr, 1))

## Example

import numpy as np import numpy.ma as ma # The numpy.ufunc has functions that operate element by element on whole arrays. # ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility # Create a 2d array # The numpy.eye() returns a 2-D array with 1’s as the diagonal and 0’s elsewhere. arr = np.eye(3) # Display the array print("Array...

", arr) # Get the type of the array print("

Our Array type...

", arr.dtype) # Get the dimensions of the Array print("

Our Array Dimensions...

",arr.ndim) # To Accumulate the result of applying the operator to all elements, use the numpy.accumulate() method in Python Numpy # For a multi-dimensional array, accumulate is applied along only one axis # Add accumulate # Accumulate along axis 1 (columns) # Add accumulate print("

Add accumulate...

",np.add.accumulate(arr, 1)) # Multiply accumulate print("

Multiply accumulate...

",np.multiply.accumulate(arr, 1))

## Output

Array... [[1. 0. 0.] [0. 1. 0.] [0. 0. 1.]] Our Array type... float64 Our Array Dimensions... 2 Add accumulate... [[1. 1. 1.] [0. 1. 1.] [0. 0. 1.]] Multiply accumulate... [[1. 0. 0.] [0. 0. 0.] [0. 0. 0.]]

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