Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
Python Articles
Page 322 of 852
Divide one polynomial by another in Python
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 MoreArray axis summations with Einstein summation convention in Python
The einsum() method evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a simple fashion. In implicit mode einsum computes these values. In explicit mode, einsum provides further flexibility to compute other array operations that might not be considered classical Einstein summation operations, by disabling, or forcing summation over specified subscript labels.For Array axis summations (sum over an axis) with Einstein summation convention, use the numpy.einsum() method in Python. The 1st parameter is the subscript. It specifies the subscripts for summation as comma separated list ...
Read MoreExtract the diagonal of a matrix with Einstein summation convention in Python
The einsum() method evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a simple fashion. In implicit mode einsum computes these values.In explicit mode, einsum provides further flexibility to compute other array operations that might not be considered classical Einstein summation operations, by disabling, or forcing summation over specified subscript labels. To extract the diagonal of a matrix with Einstein summation convention, use the numpy.einsum() method in Python.The 1st parameter is the subscript. It specifies the subscripts for summation as comma separated list of subscript ...
Read MoreGet the trace of a matrix with Einstein summation convention in Python
The einsum() method evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a simple fashion. In implicit mode einsum computes these values.In explicit mode, einsum provides further flexibility to compute other array operations that might not be considered classical Einstein summation operations, by disabling, or forcing summation over specified subscript labels.To get the trace of a matrix with Einstein summation convention, use the numpy.einsum() method in Python. The 1st parameter is the subscript. It specifies the subscripts for summation as comma separated list of subscript ...
Read MoreReturn the angle of the complex argument in Python
To return the angle of the complex argument, use the numpy.angle() method in Python. The method returns the counterclockwise angle from the positive real axis on the complex plane in the range (-pi, pi], with dtype as numpy.float64. The 1st parameter z, A complex number or sequence of complex numbers. The 2nd parameter, deg, return angle in degrees if True, radians if False (default).StepsAt first, import the required libraries −import numpy as npCreate an array using the array() method −arr = np.array([1.0, 1.0j, 1+1j]) Display the array −print("Array...", arr)Get the type of the array −print("Our Array type...", arr.dtype) Get the ...
Read MoreReturn the bases when first array elements are raised to powers from second array in Python
To return the bases when first array elements are raised to powers from second array, use the float_power() method in Python Numpy. The method returns the bases in x1 raised to the exponents in x2. This is a scalar if both x1 and x2 are scalars. The parameter x1 are the bases. The parameter x2 are the exponents.Raise each base in x1 to the positionally-corresponding power in x2. x1 and x2 must be broadcastable to the same shape. This differs from the power function in that integers, float16, and float32 are promoted to floats with a minimum precision of float64 ...
Read MoreReturn a boolean array which is True where the string element in array starts with prefix in Python
To return a boolean array which is True where the string element in array starts with prefix, use the numpy.char.startswith() method in Python Numpy. The first parameter is the input array. The second parameter is the prefix.StepsAt first, import the required libraries −import numpy as npCreate a One-Dimensional array of strings −arr = np.array(['KATIE', 'JOHN', 'KATE', 'KmY', 'BRAD']) 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 number of elements of the Array −print("Number of elements in the Array...", ...
Read MoreReturn the multiple vector cross product of two vectors and change the orientation of the result in Python
To compute the cross product of two vectors, use the numpy.cross() method in Python Numpy. The method returns c, the Vector cross product(s). The 1st parameter is a, the components of the first vector(s). The 2nd parameter is b, the components of the second vector(s). The 3rd parameter is axisa, the axis of a that defines the vector(s). By default, the last axis. The 4th parameter is axisb, the axis of b that defines the vector(s). By default, the last axis.The 5th parameter is axisc, the axis of c containing the cross product vector(s). Ignored if both input vectors have ...
Read MoreGenerate a Pseudo Vandermonde matrix of Hermite polynomial and x, y, z floating array of points in Python
To generate a pseudo Vandermonde matrix of the Hermite polynomial and x, y, z sample points, use the hermite.hermvander3d() in Python Numpy. The method returns the pseudo-Vandermonde matrix. The parameter, x, y, z are arrays of point coordinates, all of the same shape. The dtypes will be converted to either float64 or complex128 depending on whether any of the elements are complex. Scalars are converted to 1-D arrays. The parameter, deg is the list of maximum degrees of the form [x_deg, y_deg, z_deg].StepsAt first, import the required libraries −import numpy as np from numpy.polynomial import hermite as HCreate arrays of ...
Read MoreEvaluate a 2-D polynomial on the Cartesian product of x and y with 1d array of coefficient in Python
To evaluate a 2-D polynomial on the Cartesian product of x and y, use the polynomial.polygrid2d(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 1st parameter, x and y, are 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 2nd parameter, c ...
Read More