Most of us would be familiar with the term inverse while operating with matrices. But what on earth is a pseudo-inverse? If it is pseudo which in turn means a false entity, then why bother using it? This seemingly contradicting…
Finding an inverse is one of the peculiar operations to be carried out in the field of Mathematics. In this article, we shall explore one such function from the numpy library to its length & breadth. This function is used to…
Digital electronics always rely on processing signals for their routine functioning. The support from Python extends to this part of the spectrum too! The operation of combining signals is known as convolution and Python has an exclusive function to carry…
Working with matrices is always fascinating. The numpy library has a ton of functions that helps with carrying out complicated calculations using matrices. In this article, we shall demonstrate one such function that decomposes a given matrix into a pair…
This article will talk about the Numpy i0 function. The year was 1817. It was a fine evening when a German astronomer by the name of Friedrich Wilhelm Bessel was taking a closer look at the movement of planets. Well,…
In this article, we will understand and implement numpy.interp() which is a NumPy function. When given discrete data points (xp, fp), this function returns the one-dimensional piecewise linear interpolant to that function, which is evaluated at x. What is Numpy interp? numpy.interp() calculates…
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…
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 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…
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…