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Reduce a multi-dimensional array and multiply elements 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.
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. 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.
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 (multiply)...
",np.multiply.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
print("
Result (multiply)...
",np.multiply.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 (multiply)... [[ 0 190 440] [ 756 1144 1610] [2160 2800 3536]]
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