Programming Articles - Page 718 of 3366

To return the minimum of an array or minimum ignoring any NaNs, use the numpy.nanmin() method in Python. The method returns an array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned.The 1st parameter, a is an array containing numbers whose minimum is desired. If a is not an array, a conversion is attempted.The 2nd parameter, axis is an axis or axes along which the minimum is computed. The default is to compute the minimum ... Read More

To compute the condition number of a matrix in linear algebra, use the numpy.linalg.cond() method in Python. This method is capable of returning the condition number using one of seven different norms, depending on the value of p. Returns the condition number of the matrix. May be infinite.The condition number of x is defined as the norm of x times the norm of the inverse of x; the norm can be the usual L2-norm or one of a number of other matrix norms. The 1st parameter is x, the matrix whose condition number is sought. The 2nd parameter is p, ... Read More

To compute the condition number of a matrix in linear algebra, use the numpy.linalg.cond() method in Python. This method is capable of returning the condition number using one of seven different norms, depending on the value of p.Returns the condition number of the matrix. May be infinite. The condition number of x is defined as the norm of x times the norm of the inverse of x; the norm can be the usual L2-norm or one of a number of other matrix norms. The 1st parameter is x, the matrix whose condition number is sought. The 2nd parameter is p, ... Read More

To return the imaginary part of the complex argument, use the numpy.imag() method in Python. The method returns the imaginary component of the complex argument. If val is real, the type of val is used for the output. If val has complex elements, the returned type is float. The 1st parameter, val is the input array. We will also update the imaginary part of the complex argument using array.img.StepsAt first, import the required libraries −import numpy as npCreate an array using the array() method −arr = np.array([36.+1.j , 27.+2.j , 68.+3.j , 23.+2.j]) Display the array −print("Our Array...", arr)Check the ... Read More

To return the maximum of an array or maximum ignoring any NaNs, use the numpy.nanmax() method in Python. The method returns an array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned. The 1st parameter, a is an array containing numbers whose maximum is desired. If a is not an array, a conversion is attempted.The 2nd parameter, axis is an axis or axes along which the maximum is computed. The default is to compute the ... Read More

To return the maximum of an array or maximum ignoring any NaNs, use the numpy.nanmax() method in Python. The method returns an array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as a is returned. The 1st parameter, a is an array containing numbers whose maximum is desired. If a is not an array, a conversion is attempted. The 2nd parameter, axis is an axis or axes along which the maximum is computed. The default is to compute ... Read More

To replace NaN with zero and infinity with large finite numbers, use the numpy.nan_to_num() method in Python. The method returns, x, with the non-finite values replaced. If copy is False, this may be x itself. The 1st parameter is the input data. The 2nd parameter is copy, whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True.The 3rd parameter is nan, the value to be used to fill NaN values. If no value is passed then NaN values ... Read More

To return the discrete linear convolution of two one-dimensional sequences, use the numpy.convolve() method in Python Numpy. The convolution operator is often seen in signal processing, where it models the effect of a linear time-invariant system on a signal. In probability theory, the sum of two independent random variables is distributed according to the convolution of their individual distributions. If v is longer than a, the arrays are swapped before computation.The method returns the Discrete, linear convolution of a and v. The 1st parameter, a (N, ) is the first one-dimensional input array. The 2nd parameter, v (M, ) is ... Read More

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 compute a matrix transpose 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 labels. ... Read More

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 More