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To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, x, if x is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, x or its elements must support addition and multiplication with themselves and with the elements of c.The 2nd parameter, C, an array of coefficients ordered so that the coefficients for terms of degree n are contained in c[n]. If c is multidimensional the remaining indices enumerate multiple polynomials. In the two dimensional case the coefficients ... Read More

To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, x, if x is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, x or its elements must support addition and multiplication with themselves and with the elements of c.The 2nd parameter, C, an array of coefficients ordered so that the coefficients for terms of degree n are contained in c[n]. If c is multidimensional the remaining indices enumerate multiple polynomials. In the two dimensional case the coefficients ... Read More

To check if the data present in the series is monotonically decreasing or not, we can use the is_monotonic_decreasing property of the pandas Series constructor.The monotonically decreasing data is nothing but continuously decreasing values. And the attribute “is_monotonic_decreasing” is used to verify that the data in a given series object is always decreasing or not. And this attribute returns a boolean value as an output.Example 1import pandas as pd # create a series s = pd.Series([100, 57, 23, 10, 5]) print(s) print("Is monotonically decreasing: ", s.is_monotonic_decreasing)ExplanationHere, we initialized a Series with a python list of integer values ... Read More

To evaluate a Hermite_e series at points x, use the hermite.hermeval() method in Python Numpy. The 1st parameter, x, if x is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, x or its elements must support addition and multiplication with themselves and with the elements of c.The 2nd parameter, C, an array of coefficients ordered so that the coefficients for terms of degree n are contained in c[n]. If c is multidimensional the remaining indices enumerate multiple polynomials. In the two dimensional case the coefficients ... Read More

To check if the data in the series is monotonically increasing or not, we can use the is_monotonic attribute of the pandas Series constructor.The monotonically increasing is nothing but continuously increasing data. And the attribute “is_monotonic” is used to verify that the data in a given series object is always increasing or not.In the pandas series constructor, we have another monotonic attribute for checking data increment which is nothing but is_monotonic_increasing (alias for is_monotonic).Example 1# importing required packages import pandas as pd import numpy as np # creating pandas Series object series = pd.Series(np.random.randint(10, 100, 10)) print(series) print("Is ... Read More

To generate a Legendre series, use the polynomial.legendre.legfromroots() method in Python. The method returns a 1-D array of coefficients. If all roots are real then out is a real array, if some of the roots are complex, then out is complex even if all the coefficients in the result are real. The parameter roots are the sequence containing the roots.StepsAt first, import the required library −import numpy as np from numpy.polynomial import legendre as LTo generate a Legendre series, use the polynomial.legendre.legfromroots() method in Python −print("Result...", L.legfromroots((-1, 0, 1)))Get the datatype −print("Type...", L.legfromroots((-1, 0, 1)).dtype)Get the shape −print("Shape...", L.legfromroots((-1, 0, ... Read More

The pandas series constructor has an apply() which accepts any user-defined function that applies to the values of the given series object.In the same way, we can apply an anonymous function over a pandas series object. We can use this apply() method on both the pandas data structures DataFrame and Series. It Performs element-wise transformations and returns a new series object as a result.Example 1# import pandas package import pandas as pd import numpy as np # create a pandas series s = pd.Series(np.random.randint(10, 20, 5)) print(s) # Applying an anonymous function result = s.apply(lambda x: x**2) print('Output ... 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 generate a pseudo Vandermonde matrix of the Legendre polynomial, use the polynomial.legvander() method in Python Numpy. The method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where The last index is the degree of the corresponding Legendre polynomial. The dtype will be the same as the converted x.The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of ... Read More

To generate a pseudo Vandermonde matrix of the Legendre polynomial, use the polynomial.legvander() method in Python NumpyThe method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1, ), where The last index is the degree of the corresponding Legendre polynomial. The dtype will be the same as the converted x.The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the ... Read More