verifyEqual

Class: matlab.unittest.qualifications.Verifiable
Package: matlab.unittest.qualifications

Verify value is equal to specified value

Syntax

verifyEqual(verifiable,actual,expected) verifyEqual(___,Name,Value) verifyEqual(___,diagnostic)

Description

verifyEqual(verifiable,actual,expected) verifies that actual is strictly equal to expected. If expected is not a MATLAB^® or Java^® object, actual and expected must have the same class, size, and value for the verification to pass. verifyEqual compares actual and expected in the same way as the IsEqualTo constraint.

verifyEqual(___,Name,Value) verifies equality with additional options specified by one or more Name,Value pair arguments.

verifyEqual(___,diagnostic) also displays the diagnostic information in diagnostic upon a failure

Input Arguments

`verifiable`	The `matlab.unittest.TestCase` instance which is used to pass or fail the verification in conjunction with the test running framework.
`actual`	The value to test.
`expected`	Expected value.
`diagnostic`	Diagnostic information related to the qualification, specified as one of the following: string array character array function handle `matlab.unittest.diagnostics.Diagnostic` object Diagnostic values can be nonscalar. For more information, see `matlab.unittest.diagnostics.Diagnostic`.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

'AbsTol'

Absolute tolerance, specified as a numeric array. The tolerance is applied only to values of the same data type. The value can be a scalar or array the same size as the actual and expected values.

For an absolute tolerance to be satisfied, abs(expected-actual) <= absTol must be true.

'RelTol'

Relative tolerance, specified as a numeric array. The tolerance is applied only to values of the same data type. The value can be a scalar or array the same size as the actual and expected values.

For a relative tolerance to be satisfied, abs(expected-actual) <= relTol.*abs(expected) must be true.

Examples

expand all

Compare Numeric Values

Numeric values are equal if they are of the same class with equivalent size, complexity, and sparsity.

At the command prompt, create a test case for interactive testing.

testCase = matlab.unittest.TestCase.forInteractiveUse;

Verify that a numeric value is equal to itself.

verifyEqual(testCase,5,5)

Verification passed.

Verify if actual and expected values have equal sizes.

verifyEqual(testCase,[5 5],5)

Verification failed.
    ---------------------
    Framework Diagnostic:
    ---------------------
    verifyEqual failed.
    --> Sizes do not match.
        
        Actual size:
             1     2
        Expected size:
             1     1
    
    Actual Value:
         5     5
    Expected Value:
         5

Test Classes

Verify if an int8 is equal to an int16.

testCase = matlab.unittest.TestCase.forInteractiveUse;
verifyEqual(testCase,int8(5),int16(5))

Verification failed.
    ---------------------
    Framework Diagnostic:
    ---------------------
    verifyEqual failed.
    --> Classes do not match.
        
        Actual Class:
            int8
        Expected Class:
            int16
    
    Actual Value:
      int8
    
       5
    Expected Value:
      int16
    
       5

Test Cell Arrays

Elements of equal cell arrays must match in class, size, and value.

Verify that a cell array is equal to itself.

testCase = matlab.unittest.TestCase.forInteractiveUse;
verifyEqual(testCase,{'cell',struct,5},{'cell',struct,5})

Verification passed.

Test Numeric Tolerances

Verify if 4.95 is equal to 5.

testCase = matlab.unittest.TestCase.forInteractiveUse;
verifyEqual(testCase,4.95,5)

Verification failed.
    ---------------------
    Framework Diagnostic:
    ---------------------
    verifyEqual failed.
    --> The numeric values are not equal using "isequaln".
    --> Failure table:
            Actual    Expected           Error              RelativeError    
            ______    ________    ___________________    ____________________
        
             4.95        5        -0.0499999999999998    -0.00999999999999996
    
    Actual Value:
       4.950000000000000
    Expected Value:
         5

Verify that the difference between the actual value 1.5 and the expected value 2 is within 1.

verifyEqual(testCase,1.5,2,'AbsTol',1)

Verification passed.

Verify if the difference between the actual and expected values is less than 10%. Display the diagnostic information upon failure.

verifyEqual(testCase,1.5,2,'RelTol',0.1,...
    'Difference between actual and expected exceeds relative tolerance')

Verification failed.
    ----------------
    Test Diagnostic:
    ----------------
    Difference between actual and expected exceeds relative tolerance
    ---------------------
    Framework Diagnostic:
    ---------------------
    verifyEqual failed.
    --> The numeric values are not equal using "isequaln".
    --> The error was not within relative tolerance.
    --> Failure table:
            Actual    Expected    Error    RelativeError    RelativeTolerance
            ______    ________    _____    _____________    _________________
        
             1.5         2        -0.5         -0.25               0.1       
    
    Actual Value:
       1.500000000000000
    Expected Value:
         2

Tips

This method is functionally equivalent to any of the following:

import matlab.unittest.constraints.IsEqualTo;
verifiable.verifyThat(actual, IsEqualTo(expected));

import matlab.unittest.constraints.IsEqualTo;
import matlab.unittest.constraints.AbsoluteTolerance;
verifiable.verifyThat(actual, IsEqualTo(expected, ...
    'Within', AbsoluteTolerance(abstol)));

import matlab.unittest.constraints.IsEqualTo;
import matlab.unittest.constraints.RelativeTolerance;
verifiable.verifyThat(actual, IsEqualTo(expected, ...
    'Within', RelativeTolerance(reltol)));

import matlab.unittest.constraints.IsEqualTo;
import matlab.unittest.constraints.AbsoluteTolerance;
import matlab.unittest.constraints.RelativeTolerance;
verifiable.verifyThat(actual, IsEqualTo(expected, ...
    'Within', AbsoluteTolerance(abstol) | RelativeTolerance(reltol)));

There exists more functionality when using the IsEqualTo, AbsoluteTolerance, and RelativeTolerance constraints directly via verifyThat.

Use verification qualifications to produce and record failures without throwing an exception. Since verifications do not throw exceptions, all test content runs to completion even when verification failures occur. Typically verifications are the primary qualification for a unit test since they typically do not require an early exit from the test. Use other qualification types to test for violation of preconditions or incorrect test setup. Alternatively,
- Use assumption qualifications to ensure that the test environment meets preconditions that otherwise do not result in a test failure. Assumption failures result in filtered tests, and the testing framework marks the tests as Incomplete. For more information, see matlab.unittest.qualifications.Assumable.
- Use assertion qualifications when the failure condition invalidates the remainder of the current test content, but does not prevent proper execution of subsequent test methods. A failure at the assertion point renders the current test method as failed and incomplete. For more information, see matlab.unittest.qualifications.Assertable.
- Use fatal assertion qualifications to abort the test session upon failure. These qualifications are useful when the failure mode is so fundamental that there is no point in continuing testing. These qualifications are also useful when fixture teardown does not restore the MATLAB state correctly and it is preferable to abort testing and start a fresh session. For more information, see matlab.unittest.qualifications.FatalAssertable.

Documentation