总之，测试函数可以极大地增强编写测试的简便性。
Above all, test functions vastly enhance what might be called the writability of tests.
测试函数直接运行，但是对于测试类，还必须搜索方法。
Test functions simply get run, but test classes have to be searched for methods.
在大多数情况下，简单的测试函数对测试代码来说已经足够了。
In most cases, simple test functions are more than adequate for testing code.
测试函数和工程应用实例验证了该方法的有效性。
The constraint optimization problem was turned into non-constraint optimization problem by penalty function method, and multidisciplinary feasible method was used as optimization method.
用几个典型测试函数的数值实验数据验证了分析结果。
The conclusions are verified by the numerical experimental results of several test functions.
如果这样做，则会自动导出所有测试函数并通过下面的代码运行它们。
If you do this, all your test functions will be automatically exported and run via the test function shown below.
在向资源添加实现代码前，创建一些新的类来提供足够实现以测试函数。
Before adding implementation code to the resource, create a few classes that provide enough implementation to test the functions.
疗效评估包括几个视觉包括最佳矫正视力及视野测试函数的参数。
Efficacy assessments included several visual function parameters including best-corrected visual acuity and visual field testing.
然后，通过分析选用两个经典测试函数验证了MABC算法的有效性。
Then two test functions are selected in the simulation experiments through analysis, and the results verify the feasibility of MABC algorithm.
正如你期望的那样，testrunner加载测试页面，调用每个测试函数。
As you might expect the test runner loads the test page, and calls each test function.
通过测试函数表明该算法具有较好的收敛速度和稳定性，求解结果非常好。
The test functions show that the algorithm has better convergence speed and stability, the solving result is excellent.
首先定义一个HTML文件来实例化此doh、小部件，然后定义要执行的测试函数。
Well, you define an HTML file that instantiates the DOH, instantiates widgets, then defines the test functions to execute.
两个测试函数和FIR数字滤波器设计的实验结果说明这种改进的有效性。
Experimental results of two testing functions and a FIR digital filter design show the validity of the improvement on fitness evaluation.
由实验结果可知，随机性适中的TIGA算法对各测试函数的寻优能力最好。
Results show that that the search ability of TIGA algorithm, whose random degree is neither the highest nor the lowest, is the best among the tested sister algorithms.
运用标准测试函数对算法进行了测试，结果表明算法具有高质量的搜索效率和精度。
The tests on standard test functions indicate that the algorithm has high search efficiency and accuracy.
实验中用10个20 ~ 10 000维的标准测试函数对算法性能进行了测试。
In the experiments, 10 benchmark functions with 20 ~ 10 000 dimensions are used to validate the performance.
您只需将测试函数传递给getTestCallback，而它反过来包含了所想执行的断言。
You just need to pass your test function to getTestCallback, which, in turn, contains the assertions that you want to execute.
标准测试函数的特性与选择，改进粒子群算法与标准粒子群算法的比较实验与结果分析；
The features and options of Standard test functions, The comparative experiment and the results analyzing of the improved standard particle swarm algorithm and particle swarm optimization ;
文中采用30维经典测试函数及齿轮减速器优化问题作为算例，验证了该算法的优越性能。
Proved by classical testing function with 30 dimensions and gear-driven moderator, the algorithm has excellent performance.
与标准粒子群算法在四个典型测试函数上进行了比较，实验结果表明该算法有很好的潜力找到更好的解。
Compared with standard Particle Swarm Optimization in four typical test functions, results show that our algorithm has potential to find a better solution.
然后运用多种测试函数对模型进行测试，研究关键变量对系统行为的影响规律，并对其做出合理的解释。
Then using many kinds of tests function tot test the model, researched key variable how to influent the system behavior and made the reasonable explanation to it.
更进一步，如果采用简单的做法编写测试函数(如上所述)，那么测试至少能够在py . test和nose中运行。
Going a step further, if you adopt the simpler and sleeker practice of writing test functions (as described above), then your tests will at least work under both py.test and nose.
四个典型测试函数的仿真实验表明，该算法显著加快了遗传算法的寻优速度，提高了遗传算法定位最优解的精度。
The simulations on four typical test functions indicate that the proposed algorithm can greatly improve the efficiency and precision in searching the optimum value.
并且，针对该框架使用通用遗传算法测试函数，在由两台双至强处理器的工作站组成的COW集群上进行了测试。
To testify its validity, we used the standard GA test function running on a COW cluster consisting of two double Xeon workstations.
并且，针对该框架使用通用遗传算法测试函数，在由两台双至强处理器的工作站组成的COW集群上进行了测试。
To testify its validity, we used the standard GA test function running on a COW cluster consisting of two double Xeon workstations.
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