Python | numpy.assert_allclose() method Last Updated : 17 Sep, 2019 Comments Improve Suggest changes Like Article Like Report With the help of numpy.assert_allclose() method, we can get the assertion errors when two array objects are not equal upto the mark by using numpy.assert_allclose(). Syntax : numpy.assert_allclose(actual_array, desired_array) Return : Return the Assertion error if two array objects are not equal. Example #1 : In this example we can see that using numpy.assert_allclose() method, we are able to get the assertion error if two arrays are not equal. Python3 1=1 # import numpy import numpy as np # using numpy.assert_allclose() method gfg1 = [1, 2, 3] gfg2 = np.array(gfg1) if np.testing.assert_allclose(gfg1, gfg2): print("Matched") Output : Matched Example #2 : Python3 1=1 # import numpy import numpy as np # using numpy.assert_allclose() method gfg1 = [1, 2, 3] gfg2 = np.array([4, 5, 6]) print(np.testing.assert_allclose(gfg1, gfg2)) Output : Mismatch: 100% Max absolute difference: 3 Max relative difference: 0.75 gfg1: array([1, 2, 3]) gfg2: array([4, 5, 6]) Comment More infoAdvertise with us Next Article Python | numpy.assert_allclose() method J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Practice Tags : python Similar Reads Python | Numpy np.assert_almost_equal() method With the help of np.assert_almost_equal() method, we can get the assertion error if two items are not equal up to desired precision value by using np.assert_almost_equal() method. Syntax : np.assert_almost_equal(actual, desired, decimal) Return : Return the assertion error if two values are not equa 1 min read numpy.allclose() in Python numpy.allclose() function is used to find if two arrays are element-wise equal within a tolerance. The tolerance values are positive, typically very small numbers. The relative difference (rtol * abs(arr2)) and the absolute difference atol are added together to compare against the absolute differenc 4 min read Python | Numpy np.assert_array_almost_equal() method With the help of np.assert_array_almost_equal() method, we can get the assertion error if two array objects are not equal up to desired precision value by using np.assert_array_almost_equal() method. Syntax : np.assert_array_almost_equal(actual, desired, decimal) Return : Return the assertion error 1 min read Python | Numpy np.assert_approx_equal() method With the help of np.assert_approx_equal() method, we can get the assertion error if two items are not equal up to significant digits by using np.assert_approx_equal() method. Syntax : np.assert_approx_equal(actual, desired, significant) Return : Return the assertion error if two values are not equal 1 min read Python | Numpy np.assert_array_less() method With the help of np.assert_array_less() method, we can get the assertion error if two array like objects are not ordered by less than by using np.assert_array_less() method. Syntax : np.assert_array_less(x, y) Return : Return assertion error if two array objects are unequal. Example #1 : In this exa 1 min read numpy.ma.allclose() function - Python numpy.ma.allclose() function returns True if two arrays are element-wise equal within a tolerance. This function is equivalent to allclose except that masked values are treated as equal (default) or unequal, depending on the masked_equal argument. Syntax : numpy.ma.allclose(a, b, masked_equal = True 2 min read Python | Numpy np.assert_equal() method With the help of np.assert_equal() method, we can get the assertion error when two objects are not equal by using np.assert_equal() method. Syntax : np.assert_equal(actual, desired) Return : Return assertion error if two object are unequal. Example #1 : In this example we can see that by using np.as 1 min read Python | Numpy np.assert_array_equal() method With the help of np.assert_array_equal() method, we can get the assertion error if two array like objects are not equal by using np.assert_array_equal() method. Syntax : np.assert_array_equal(x, y) Return : Return the assertion error if two objects are not equal. Example #1 : In this example we can 1 min read Python | numpy.lookfor() method With the help of numpy.lookfor() method, we can get the information about the module in the numpy by using numpy.lookfor() method. Syntax : numpy.lookfor(module_name) Return : Return the information about the module. Example #1 : In this example we can see that by using numpy.lookfor() method, we ar 1 min read Python | os.closerange() method OS module in Python provides functions for interacting with the operating system. OS comes under Python’s standard utility modules. This module provides a portable way of using operating system dependent functionality. os.closerange() method in Python is used to close all file descriptors in the ran 2 min read Like