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Reduce a Multi-Dimensional Array in NumPy
To reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy. Here, we have used multiply.reduce() to reduce it to the multiplication of elements.
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-byelement 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 multi-dimensional array −
arr = np.arange(27).reshape((3,3,3))
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 reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy. Here, we have used multiply.reduce() to reduce it to the multiplication of elements −
print("
Result (multiplication)...
",np.multiply.reduce(arr))
To reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy. Here, we have used add.reduce() to reduce it to the addition of elements −
print("
Result (addition)...
",np.add.reduce(arr))
Example
import numpy as np # 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 multi-dimensional array arr = np.arange(27).reshape((3,3,3)) # 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 reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy # Here, we have used multiply.reduce() to reduce it to the multiplication of elements elements print("
Result (multiplication)...
",np.multiply.reduce(arr)) # To reduce a multi-dimensional array, use the np.ufunc.reduce() method in Python Numpy # Here, we have used add.reduce() to reduce it to the addition of elements print("
Result (addition)...
",np.add.reduce(arr))
Output
Array... [[[ 0 1 2] [ 3 4 5] [ 6 7 8]] [[ 9 10 11] [12 13 14] [15 16 17]] [[18 19 20] [21 22 23] [24 25 26]]] Our Array type... int64 Our Array Dimensions... 3 Result (multiplication)... [[ 0 190 440] [ 756 1144 1610] [2160 2800 3536]] Result (addition)... [[27 30 33] [36 39 42] [45 48 51]]