To differentiate a Chebyshev series, use the polynomial.chebder() method in Python Numpy. The method returns the Chebyshev series of the derivative. Returns the Chebyshev series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl. The argument c is an array of coefficients from low to high degree along each axis, e.g., [1, 2, 3] represents the series 1*T_0 + 2*T_1 + 3*T_2 while [[1, 2], [1, 2]] represents 1*T_0(x)*T_0(y) + 1*T_1(x)*T_0(y) + 2*T_0(x)*T_1(y) + 2*T_1(x)*T_1(y) if axis=0 is x and axis=1 is y.The 1st parameter is c, an array of Chebyshev series coefficients. ... Read More

To differentiate a Chebyshev series, use the polynomial.chebder() method in Python Numpy. The method returns the Chebyshev series of the derivative. Returns the Chebyshev series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl. The argument c is an array of coefficients from low to high degree along each axis, e.g., [1, 2, 3] represents the series 1*T_0 + 2*T_1 + 3*T_2 while [[1, 2], [1, 2]] represents 1*T_0(x)*T_0(y) + 1*T_1(x)*T_0(y) + 2*T_0(x)*T_1(y) + 2*T_1(x)*T_1(y) if axis=0 is x and axis=1 is y.The 1st parameter is c, an array of Chebyshev series coefficients. ... Read More

To differentiate a Chebyshev series, use the polynomial.chebder() method in Python Numpy. The method returns the Chebyshev series of the derivative. Returns the Chebyshev series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl. The argument c is an array of coefficients from low to high degree along each axis, e.g., [1, 2, 3] represents the series 1*T_0 + 2*T_1 + 3*T_2 while [[1, 2], [1, 2]] represents 1*T_0(x)*T_0(y) + 1*T_1(x)*T_0(y) + 2*T_0(x)*T_1(y) + 2*T_1(x)*T_1(y) if axis=0 is x and axis=1 is y.The 1st parameter is c, an array of Chebyshev series coefficients. ... Read More

To evaluate a 3-D Chebyshev series on the Cartesian product of x, y, z, use the polynomial.chebgrid3d(x, y, z) method in Python. If c has fewer than three dimensions, ones are implicitly appended to its shape to make it 3-D. The shape of the result will be c.shape[3:] + x.shape + y.shape + z.shape.The parameter, x, y and z are the three dimensional series is evaluated at the points in the Cartesian product of x, y, and z. If x, `y`, or z is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged ... Read More

To evaluate a 2-D Chebyshev series on the Cartesian product of x and y, use the polynomial.chebgrid2d(x, y, c) method in Python. The method returns the values of the two dimensional Chebyshev series at points in the Cartesian product of x and y. If c has fewer than two dimensions, ones are implicitly appended to its shape to make it 2-D. The shape of the result will be c.shape[2:] + x.shape + y.shape.The parameter, x and y are the two dimensional series is evaluated at the points in the Cartesian product of x and y. If x or y is ... Read More

To compute the roots of a polynomials, use the polynomial.polyroots() method in Python Numpy. The method returns an array of the roots of the polynomial. If all the roots are real, then out is also real, otherwise it is complex. The parameter, c is a 1-D array of polynomial coefficients.The root estimates are obtained as the eigenvalues of the companion matrix, Roots far from the origin of the complex plane may have large errors due to the numerical instability of the power series for such values. Roots with multiplicity greater than 1 will also show larger errors as the value ... Read More

To compute the roots of a polynomials, use the polynomial.polyroots() method in Python Numpy. The method returns an array of the roots of the polynomial. If all the roots are real, then out is also real, otherwise it is complex. The parameter, c is a 1-D array of polynomial coefficients.The root estimates are obtained as the eigenvalues of the companion matrix, Roots far from the origin of the complex plane may have large errors due to the numerical instability of the power series for such values. Roots with multiplicity greater than 1 will also show larger errors as the value ... Read More

To generate a monic polynomial with given complex roots, use the polynomial.polyfromroots() method in Python Numpy. The method returns the 1-D array of the polynomial’s coefficients If all the roots are real, then out is also real, otherwise it is complex. The parameter roots are the sequence containing the roots.StepsAt first, import the required libraries -from numpy.polynomial import polynomial as PGiven complex roots −j = complex(0, 1) print("Result...", P.polyfromroots((-j, j)))Get the datatype −print("Type...", P.polyfromroots((-j, j)).dtype) Get the shape −print("Shape...", P.polyfromroots((-j, j)).shape)Examplefrom numpy.polynomial import polynomial as P # To generate a monic polynomial with given roots, use the polynomial.polyfromroots() method ... Read More

To evaluate a 3-D Chebyshev series at points (x, y, z), use the polynomial.chebval3d() method in Python Numpy. The method returns the values of the multidimensional polynomial on points formed with triples of corresponding values from x, y, and z.The parameters are x, y, z. The three dimensional series is evaluated at the points (x, y, z), where x, y, and z must have the same shape. If any of x, y, or z is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged and if it isn’t an ndarray it is treated ... Read More

To evaluate a Evaluate a 3-D Chebyshev series at points (x, y, z), use the polynomial.chebval3d() method in Python Numpy. The method returns the values of the multidimensional polynomial on points formed with triples of corresponding values from x, y, and z.The parameters are x, y, z. The three dimensional series is evaluated at the points (x, y, z), where x, y, and z must have the same shape. If any of x, y, or z is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged and if it isn’t an ndarray it ... Read More