To return matrix rank of array using Singular Value Decomposition method, use the numpy.linalg.matrix_rank() method in Python. Rank of the array is the number of singular values of the array that are greater than tol. The 1st parameter, A is the input vector or stack of matrices.The 2nd parameter, tol ... Read More

The arccosh() is a multivalued function: for each x there are infinitely many numbers z such that cosh(z) = x. The convention is to return the z whose imaginary part lies in [-pi, pi] and the real part in [0, inf]. For real-valued input data types, arccosh always returns real ... 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 ... Read More

The arcsinh is a multivalued function: for each x there are infinitely many numbers z such that sinh(z) = x. The convention is to return the z whose imaginary part lies in [-pi/2, pi/2]. For real-valued input data types, arcsinh always returns real output. For each value that cannot be ... Read More

To get the Inner product of two multi-dimensional 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 ... Read More

The arcsinh is a multivalued function: for each x there are infinitely many numbers z such that sinh(z) = x. The convention is to return the z whose imaginary part lies in [-pi/2, pi/2]. For real-valued input data types, arcsinh always returns real output. For each value that cannot be ... Read More

To compute log-determinants for a stack of matrices, use the numpy.linalg.slogdet() method in Python. The 1st parameter, s is an input array, has to be a square 2-D array. The method, with sign returns a number representing the sign of the determinant. For a real matrix, this is 1, 0, ... Read More

To compute the Hyperbolic cosine, use the numpy.cosh() method in Python Numpy. The method is equivalent to 1/2 * (np.exp(x) + np.exp(-x)) and np.cos(1j*x). Returns the corresponding hyperbolic cosine values. This is a scalar if x is a scalar. The 1st parameter, x is input array. The 2nd and 3rd ... Read More

To compute the Hyperbolic sine of the array elements, use the numpy.sinh() method in Python Numpy. The method is equivalent to 1/2 * (np.exp(x) - np.exp(-x)) or -1j * np.sin(1j*x). Returns the corresponding hyperbolic sine values. This is a scalar if x is a scalar. The 1st parameter, x is ... Read More

To convert a radian array to degrees, use the numpy.rad2deg() method in Python Numpy. The method returns the corresponding angle in degrees. This is a scalar if x is a scalar. The 1st parameter is an input angle in radians. The 2nd and 3rd parameters are optional.The 2nd parameter is ... Read More