Integrate along the given axis using the composite trapezoidal rule in Python

PythonNumpyServer Side ProgrammingProgramming

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 library −

import numpy as np

Creating a numpy array using the arange() method. We have added elements of int type −

arr = np.arange(9).reshape(3, 3)

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, axis = 0))

Example

import numpy as np

# Creating a numpy array using the arange() method
# We have added elements of int type
arr = np.arange(9).reshape(3, 3)

# 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, axis = 0))

Output

Our Array...
[[0 1 2]
[3 4 5]
[6 7 8]]

Dimensions of our Array...
2

Datatype of our Array object...
int64

Result (trapz)...
[ 6. 8. 10.]
raja
Updated on 25-Feb-2022 05:19:08

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