numpy.geomspace() returns a set of numbers spaced evenly on a log scale (a geometric progression).Linspace − It is similar to geomspace, but endpoints specified using the log and base.Logspace − It is similar to geomspace, but endpoints specified with arithmetic instead of geometric progression.Syntaxnumpy.goemspace(start, stop, num = 50, endpoint = True/False, dtype = None)ParametersThe above function can accept the following parameters −start − Start of the sequence; default is zero.stop − Endpoint of the sequence.num − Number of elements which are generated between the start and stop sequence.endpoint − It controls whether the stop value is included in the output ... Read More

numpy.logspace returns a set of numbers spaced evenly on a log scale. Its syntax is as follows −numpy.logspace(start, stop, num = 50, endpoint = True/False, base = 10.0, dtype = None)ParametersThe logspace function can accept the following parameters −start − Start of the sequence; default is zero.stop − Endpoint of the sequence.num − Number of elements to be generated between the start and stop sequence.endpoint − It controls whether the stop value is included in the output array or not. If the endpoint is True, then the stop parameter is included as the last item in the nd.array. If endpoint=false, ... Read More

The numpy.linspace function is used to create a set of evenly spaced numbers within a defined interval.Syntaxnumpy.linspace(start, stop, num = 50, endpoint = True/False, retstep = False/True, dtype = None)ParametersThe function can accept the following parameters −start − Start of the sequence; by default, it is considered as zero.stop − Endpoint of the sequence.num − Number of elements to be generated between start and stop.endpoint − It controls whether the stop value is included in the output array or not. If the endpoint is True, then the stop parameter is included as the the last item in the nd.array. If ... Read More

To differentiate a Laguerre series, use the laguerre.lagder() method in Python. The method returns the Laguerre 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*L_0 + 2*L_1 + 3*L_2 while [[1, 2], [1, 2]] represents 1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) + 2*L_0(x)*L_1(y) + 2*L_1(x)*L_1(y) if axis=0 is x and axis=1 is y.The 1st parameter, c is an array of Laguerre series coefficients. If c is multidimensional the different axis correspond ... Read More

To differentiate a Laguerre series, use the laguerre.lagder() method in Python. The method returns the Laguerre 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*L_0 + 2*L_1 + 3*L_2 while [[1, 2], [1, 2]] represents 1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) + 2*L_0(x)*L_1(y) + 2*L_1(x)*L_1(y) if axis=0 is x and axis=1 is y.The 1st parameter, c is an array of Laguerre series coefficients. If c is multidimensional the different axis correspond ... Read More

To evaluate a 3-D Laguerre series on the Cartesian product of x, y and z, use the polynomial.laguerre.laggrid3d() method in Python. The method returns the values of the three dimensional Laguerre series at points in the Cartesian product of x, y and z.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 1st parameter, x, y, z are the three dimensional series is evaluated at the points in the Cartesian product of x, y, and z. If ... Read More

To evaluate a 2-D Laguerre series on the Cartesian product of x and y, use the polynomial.laguerre.laggrid2d() method in Python. The method returns the values of the two dimensional Laguerre 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 1st parameter, x, y is the two dimensional series is evaluated at the points in the Cartesian product of x and y. If x or y is a list ... Read More

To evaluate a Laguerre series at points x, use the polynomial.laguerre.lagval() method in Python Numpy. The 1st parameter is 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 ... Read More

To evaluate a Laguerre series at points x, use the polynomial.laguerre.lagval() method in Python Numpy. The 1st parameter is 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 ... Read More

To evaluate a Laguerre series at points x, use the polynomial.laguerre.lagval() method in Python Numpy. The 1st parameter is 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 ... Read More