This article would be covering a rather strange function within the numpy library of Python. It is so strange that at prima facie one might even question its very existence. Enter the numpy.positive( ) function! It returns the element-wise numerical positive for the input array. Makes sense right? But, here is the catch! It does […]
There are many articles in AskPython detailing the various functions that the numpy library of Python has got to offer. In this article, we shall explore one which combines the logarithmic and exponential functions to the base of 2 – the logaddexp2( ) function. Let’s get things started by first importing the numpy library using the
The numpy or the numerical python library is like a gold mine of functions that can be used for computing difficult linear algebraic problems. One such function is the numpy linalg.eigh() which can be used to calculate the eigenvalues and the eigenvectors of a complex Hermitian or a real symmetric matrix. A Hermitian matrix is
Numpy linalg.eigh: Finding Eigenvalues and Vectors of Symmetric Matrices Read More »
Normalization of the matrix is to scale the elements of the matrix in such a way that their values remain between zero and one. Depending on the order of a matrix, the function linalg.norm() returns one of the seven/eight different matrix norms or in some cases one of the many infinite matrix norms depending on
Matrices in mathematics are rectangular arrangements of an array of homogeneous data types such as numbers, symbols, or expressions. They are arranged in the form of rows and columns which represents objects or some specific properties of that object. Eigenvalues are values that are scalar in type and are associated with linear matrix equations. They
Numpy linalg.eigvals – Compute the eigenvalues of a general matrix Read More »
Scientific calculations can sometimes be extremely tedious when done manually especially when they involve matrices of humongous sizes and complicated values. The Numerical Python or simply the Numpy library already contains built-in functions involving matrices and linear algebra that make computing faster and more accurate. In this article, we will dissect and look at the
Numpy linalg.inv – Compute the (multiplicative) inverse of a matrix Read More »
Linear equations are one of the most important instruments of modern mathematics. A linear equation is a mathematical equation represented in the form of a1 x1 + a2 x2 + a3 x3 + . . . . . . .+ an xn + b = 0, where x1, x2 ,x3 ……… xn are variables (or
NumPy stands for Numerical Python and provides a number of mathematical operations to operate on multidimensional matrices and arrays. This open-source package enables you to perform a wide variety of complex mathematical operations on arrays or matrices. Also read: Numpy Heaviside – Compute the Heaviside step function One such mathematical function to work on arrays
NumPy conjugate()- Return the complex conjugate, element-wise. Read More »
In this article, we learn how to calculate the Heaviside step function using numpy.heaviside() , a NumPy package function in python. We will get a stronger hold of this topic by implementing a few examples and understanding its syntax. Also read: Numpy real_if_close – If the input is complex with all imaginary parts close to
Numpy Heaviside – Compute the Heaviside step function Read More »
NumPy, which stands for “Numerical Python,” is a basic package that is mostly used with arrays and multidimensional matrices. A broad variety of functions are available in this open-source package to carry out intricate mathematical operations on arrays or matrices. One such mathematical function is the sign() function in the NumPy package, it is used
NumPy sign()- Returns an element-wise indication of the sign of a number. Read More »