Programming Articles - Page 707 of 3366

To evaluate a 2-D Hermite series on the Cartesian product of x and y, use the hermite.hermgrid2d(x, y, c) method in Python. The method returns the values of the two dimensional polynomial at points in the Cartesian product of x and y.The parameters are x, y. The two dimensional series is evaluated at the points in the Cartesian product of x and y. 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 ... Read More

To evaluate a 2D Hermite series at points (x, y), use the hermite.hermval2d() 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.The 1st parameter is 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 2nd parameter, C, ... Read More

To evaluate a Hermite series at points x, use the hermite.hermval() 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 series at points x, use the hermite.hermval() 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 series at points x, use the hermite.hermval() 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 series at points x, use the hermite.hermval() 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 add one Hermite series to another, use the polynomial.hermite.hermadd() method in Python Numpy. The method returns an array representing the Hermite series of their sum. Returns the sum of two Hermite 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 series coefficients ordered from low to high.StepsAt first, import the required library −import numpy as np from numpy.polynomial import hermite as HCreate 1-D arrays of Hermite series coefficients −c1 ... Read More

To return the cumulative product of array elements over a given axis treating NaNs as one, use the nancumprod() method. The cumulative product does not change when NaNs are encountered and leading NaNs are replaced by ones. Ones are returned for slices that are all-NaN or empty. The method returns a new array holding the result is returned unless out is specified, in which case it is returned. Cumulative works like, 5, 5*10, 5*10*15, 5*10*15*20The 1st parameter is the input array. The 2nd parameter is the Axis along which the cumulative product is computed. By default the input is flattened. ... Read More

To return a boolean array which is True where the string element in array ends with suffix, use the numpy.char.endswith() method in Python Numpy. The first parameter is the input array. The second parameter is the suffix. The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_StepsAt first, import the required libraries −import numpy as npCreate a One-Dimensional array of strings −arr = np.array(['KATIE', 'JOHN', 'KATE', 'AmY', 'BRADley'])Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype)Get the dimensions of the Array −print("Array Dimensions...", arr.ndim)Get the shape of the Array −print("Our Array Shape...", arr.shape)Get the ... Read More

To get the Inner product of two arrays, use the numpy.inner() method in Python. Ordinary inner product of vectors for 1-D arrays, in higher dimensions a sum product over the last axes. The parameters are 1 and b, two vectors. If a and b are nonscalar, their last dimensions must match.StepsAt first, import the required libraries −import numpy as npCreating two numpy One-Dimensional array using the array() method −arr1 = np.array([5, 10, 15]) arr2 = np.array([20, 25, 30])Display the arrays −print("Array1...", arr1) print("Array2...", arr2)Check the Dimensions of both the arrays −print("Dimensions of Array1...", arr1.ndim) print("Dimensions of Array2...", arr2.ndim)Check the Shape ... Read More