To integrate along the given axis using the composite trapezoidal rule, use the numpy.trapz() method. If x is provided, the integration happens in sequence along its elements - they are not sorted. The method returns the definite integral of ‘y’ = n-dimensional array as approximated along a single axis by the trapezoidal rule. If ‘y’ is a 1-dimensional array, then the result is a float. If ‘n’ is greater than 1, then the result is an ‘n-1’ dimensional array.
The 1st parameter, y is the input array to integrate. The 2nd parameter, x is the sample points corresponding to the y values. If x is None, the sample points are assumed to be evenly spaced dx apart. The default is None. The 3rd parameter, dx is the spacing between sample points when x is None. The default is 1. The 4th parameter, axis is the axis along which to integrate.
Steps
At first, import the required libraries −
import numpy as np
Creating a numpy array using the array() method. We have added elements of int type −
arr = np.array([20, 35])
Display the array −
print("Our Array...\n",arr)Check the Dimensions −
print("\nDimensions of our Array...\n",arr.ndim)
Get the Datatype −
print("\nDatatype of our Array object...\n",arr.dtype)To integrate along the given axis using the composite trapezoidal rule, use the numpy.trapz() method −
print("\nResult (trapz)...\n",np.trapz(arr, x = [55, 80]))
Example
import numpy as np
# Creating a numpy array using the array() method
# We have added elements of int type
arr = np.array([20, 35])
# Display the array
print("Our Array...\n",arr)
# Check the Dimensions
print("\nDimensions of our Array...\n",arr.ndim)
# Get the Datatype
print("\nDatatype of our Array object...\n",arr.dtype)
# To integrate along the given axis using the composite trapezoidal rule, use the numpy.trapz() method
print("\nResult (trapz)...\n",np.trapz(arr, x = [55, 80]))Output
Our Array... [20 35] Dimensions of our Array... 1 Datatype of our Array object... int64 Result (trapz)... 687.5