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To integrate a Legendre series, use the polynomial.legendre.legint() method in Python. The method returns the Legendre series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, is added. The scaling factor is for use in a linear change of variable. The 1st parameter, c is an array of Legendre series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.The 2nd parameter, m is an order of integration, must be positive. (Default: ... Read More
To integrate a Legendre series, use the polynomial.legendre.legint() method in Python. The method returns the Legendre series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, is added. The scaling factor is for use in a linear change of variable.The 1st parameter, c is an array of Legendre series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index. The 2nd parameter, m is an order of integration, must be positive. (Default: ... Read More
To differentiate a Legendre series, use the polynomial.laguerre.legder() method in Python. Returns the Legendre series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl.The 1st parameter, c is an array of Legendre series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.The 2nd parameter, m is the number of derivatives taken, must be non-negative. (Default: 1). The 3rd parameter, scl is a scalar. Each differentiation is multiplied by scl. The end result is multiplication by scl**m. This is for ... Read More
To multiply the Hermite_e series by x, where x is the independent variable, use the polynomial.hermite.hermemulx() method in Python Numpy. The method returns an array representing the result of the multiplication. The parameter, c is a 1-D array of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate an array −c = np.array([1, 2, 3])Display the array −print("Our Array...", c)Check the Dimensions −print("Dimensions of our Array...", c.ndim)Get the Datatype −print("Datatype of our Array object...", c.dtype)Get the Shape −print("Shape of our Array object...", c.shape)To multiply the Hermite_e ... Read More
To subtract one Hermite_e series to another, use the polynomial.hermite.hermesub() method in Python Numpy. The method returns an array representing the Hermite_e series of their difference. Returns the difference of two Hermite_e series c1 - c2. The sequences of coefficients are from lowest order term to highest, i.e., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters c1 and c2 are 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate 1-D arrays of Hermite_e series coefficients −c1 = np.array([1, ... Read More
To add one Hermite_e series to another, use the polynomial.hermite.heremadd() method in Python Numpy. The method returns an array representing the Hermite_e series of their sum. Returns the sum of two Hermite_e series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1, 2, 3] represents the series P_0 + 2*P_1 + 3*P_2. The parameters c1 and c2 are 1-D arrays of Hermite_e series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite_e as HCreate 1-D arrays of Hermite_e series coefficients −c1 ... Read More
To convert a polynomial to a Legendre series, use the legendre.poly2lag() method in Python Numpy. Convert an array representing the coefficients of a polynomial ordered from lowest degree to highest, to an array of the coefficients of the equivalent Legendre series, ordered from lowest to highest degree. The method returns a 1-D array containing the coefficients of the equivalent Legendre series. The parameter pol, is a 1-D array containing the polynomial coefficientsStepsAt first, import the required library −import numpy as np from numpy.polynomial import legendre as LCreate an array using the numpy.array() method −c = np.array([1, 2, 3, 4, 5])Display ... Read More
TestNG supports multi-threading, i.e., a @Test method can be invoked multiple times in parallel. A test method should be invoked from multiple threads so that multiple invocation is also required. If we want to run a single @Test at multi-thread, it is of no use. Therefore, multi-thread is useful if a @Test method needs to be run multiple times asynchronously.Multi-threading can be achieved by using the keyword threadPoolSize = at @Test. However, to invoke a method multiple times, another keyword invocationCount = is required. Combining these two keywords, we can achieve multi-threading. For example, @Test(threadPoolSize=5, invocationCount = 10)In this example, ... Read More
TestNG supports multiple ways to skip or ignore a @Test execution. Based on the requirement, a user can skip a complete test without executing it at all or skip a test based on a specific condition. If the condition meets at the time of execution, it skips the remaining code in the test.Following are the ways to skip the @Test execution −Use the parameter enabled=false at @Test. By default, this parameter is set as True.Use throw new SkipException(String message) to skip a test.Conditional Skip – The user can have a condition check. If the condition is met, it will throw ... Read More
TestNG supports native dependency injection. It allows to declare additional parameters in methods. At the runtime, TestNG automatically fills these parameters with the right values. Here is a list of some native dependencies in TestNG:ITestContextXmlTestMethodITestResultYou can use these dependencies to get the execution status of a test in TestNG.Usually, @AfterMethod supports all these native dependencies and the test status could be either Success, Failure or Skip.TestNG supports the following test status that can be retrieved by calling the function at the right place.org.testng.ITestResultpublic static final intFAILURE2public static final intSKIP3public static final intSTARTED16public static final intSUCCESS1public static final intSUCCESS_PERCENTAGE_FAILURE4In this article, ... Read More