To evaluate a 2-D polynomial at points (x, y), use the polynomial.polyval2d() method in Python Numpy. The method returns the values of the two dimensional polynomial at points formed with pairs of corresponding values from x and y i.e. Parameters, x, y. The two dimensional series is evaluated at the points (x, y), where x and y must have the same shape. If x or y 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 as a scalar.The parameter, c is an Array ... Read More

To evaluate a polynomial at points x, use the polynomial.polyval() method in Python. 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 may be ... Read More

To evaluate a polynomial at points x, use the polynomial.polyval() 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 may ... Read More

To raise a polynomial to a power, use the numpy.polynomial.polynomial.polypow() method in Python. Returns the polynomial c raised to the power pow. The argument c is a sequence of coefficients ordered from low to high. i.e., [1, 2, 3] is the series 1 + 2*x + 3*x**2. The method returns the array of coefficient series representing the quotient and remainder.The 1st parameter, c is a 1-D array of array of series coefficients ordered from low to high degree. The 2nd parameter, pow is a Power to which the series will be raised. The 3rd parameter, maxpower, is the maximum power ... Read More

To divide one polynomial by another, use the numpy.polynomial.polynomial.polydiv() method in Python. Returns the quotient-with-remainder of two polynomials c1 / c2. The arguments are sequences of coefficients, from lowest order term to highest, e.g., [1, 2, 3] represents 1 + 2*x + 3*x**2.The method returns the array of coefficient series representing the quotient and remainder. The parameters c1 and c2 are the 1-D arrays of coefficients representing a polynomial, relative to the “standard” basis, and ordered from lowest order term to highest.This numpy.polynomial.polynomial module provides a number of objects useful for dealing with polynomials, including a Polynomial class that encapsulates ... Read More

To return the minimum of an array or minimum ignoring any NaNs, use the numpy.nanmin() method in Python. The method returns an array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned.The 1st parameter, a is an array containing numbers whose minimum is desired. If a is not an array, a conversion is attempted.The 2nd parameter, axis is an axis or axes along which the minimum is computed. The default is to compute the minimum ... Read More

To compute the condition number of a matrix in linear algebra, use the numpy.linalg.cond() method in Python. This method is capable of returning the condition number using one of seven different norms, depending on the value of p. Returns the condition number of the matrix. May be infinite.The condition number of x is defined as the norm of x times the norm of the inverse of x; the norm can be the usual L2-norm or one of a number of other matrix norms. The 1st parameter is x, the matrix whose condition number is sought. The 2nd parameter is p, ... Read More

To compute the condition number of a matrix in linear algebra, use the numpy.linalg.cond() method in Python. This method is capable of returning the condition number using one of seven different norms, depending on the value of p.Returns the condition number of the matrix. May be infinite. The condition number of x is defined as the norm of x times the norm of the inverse of x; the norm can be the usual L2-norm or one of a number of other matrix norms. The 1st parameter is x, the matrix whose condition number is sought. The 2nd parameter is p, ... Read More

To return the imaginary part of the complex argument, use the numpy.imag() method in Python. The method returns the imaginary component of the complex argument. If val is real, the type of val is used for the output. If val has complex elements, the returned type is float. The 1st parameter, val is the input array. We will also update the imaginary part of the complex argument using array.img.StepsAt first, import the required libraries −import numpy as npCreate an array using the array() method −arr = np.array([36.+1.j , 27.+2.j , 68.+3.j , 23.+2.j]) Display the array −print("Our Array...", arr)Check the ... Read More

To return the maximum of an array or maximum ignoring any NaNs, use the numpy.nanmax() method in Python. The method returns an array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned. The 1st parameter, a is an array containing numbers whose maximum is desired. If a is not an array, a conversion is attempted.The 2nd parameter, axis is an axis or axes along which the maximum is computed. The default is to compute the ... Read More