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Numpy Articles
Page 45 of 81
Compute the eigenvalues of a complex Hermitian or real symmetric matrix in Python
To compute the eigenvalues of a complex Hermitian or real symmetric matrix, use the numpy.eigvalsh() method. The method returns the eigenvalues in ascending order, each repeated according to its multiplicity.The 1st parameter, a is a complex- or real-valued matrix whose eigenvalues are to be computed. The 2nd parameter, UPLO specifies whether the calculation is done with the lower triangular part of a (‘L’, default) or the upper triangular part (‘U’). Irrespective of this value only the real parts of the diagonal will be considered in the computation to preserve the notion of a Hermitian matrix. It therefore follows that the ...
Read MoreReturn the scalar dtype or NumPy equivalent of Python type of an object
To return the scalar dtype or NumPy equivalent of Python type of an object, use the numpy.obj2sctype() method. The 1st parameter is the object of which the type is returned The default parameter, if given, is returned for objects whose types cannot be determined. If not given, None is returned for those objects.StepsAt first, import the required library −import numpy as npTo return the scalar dtype or NumPy equivalent of Python type of an object, use the numpy.obj2sctype() method −print("Using the obj2sctype() method in Numpy")Checking for int −print("Result...", np.obj2sctype(np.array([45, 89]))) print("Result...", np.obj2sctype(np.array([389, 7985])))Checking for float −print("Result...", np.obj2sctype(np.float32)) print("Result...", np.obj2sctype(np.float64)) print("Result...", ...
Read MoreReturn True if all entries of two arrays are equal in Numpy
To return True if all entries of two arrays are equal, use the ma.allequal() method in Python Numpy. Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned.The fill_value sets whether masked values in a or b are considered equal (True) or not (False). A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether ...
Read MoreGenerate a Vandermonde matrix and set the number of columns in the output in Numpy
To generate a Vandermonde matrix, use the np.ma.vander() method in Python Numpy. Set the number of columns in the output using the N parameter. If N is not specified, a square array is returned (N = len(x)).The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector raised element-wise to the power of N - i - 1. Such a matrix with a geometric progression in each row is named for Alexandre- Theophile Vandermonde.StepsAt ...
Read MoreGenerate a Vandermonde matrix in Numpy
To generate a Vandermonde matrix, use the np.ma.vander() method in Python Numpy. A Vandermonde matrix, named after Alexandre-Théophile Vandermonde, is a matrix with the terms of a geometric progression in each row.The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector raised element-wise to the power of N - i - 1. Such a matrix with a geometric progression in each row is named for Alexandre- Theophile Vandermonde.StepsAt first, import the required library ...
Read MoreReturn the outer product of two masked arrays in Numpy
To return the outer product of two masked arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt first, import the required library −import numpy ...
Read MoreMask rows and/or columns of a 2D Numpy array that contain masked values along negative axis
To mask rows and/or columns of a 2D array that contain masked values, use the np.ma.mask_rowcols() method in Numpy. The function returns a modified version of the input array, masked depending on the value of the axis parameter.Mask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis parameter −If axis is None, rows and columns are masked.If axis is 0, only rows are masked.If axis is 1 or -1, only columns are masked.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with ...
Read MoreCompare and return True if a Numpy array is less than equal to another
To compare and return True if an array is less than equal to another, use the numpy.char.less_equal() method in Python Numpy. The arr1 and arr2 are the two input string arrays of the same shape.Unlike numpy.less_equal, this comparison is performed by first stripping whitespace characters from the end of the string. This behavior is provided for backward-compatibility with numarray.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.StepsAt first, import the required library −import numpy as npCreate two One-Dimensional arrays of string −arr1 = np.array(['Cio', 'Tom', 'Cena', 'Kate', 'Adams', 'brad', 'aa']) arr2 = ...
Read MoreCheck which element in a masked array is greater than a given value
To check which element in a masked array is greater than the given value, use the ma.MaskedArray.__gt__() method. True is returned for every array element greater than the given value val. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of ...
Read MoreCheck which element in a masked array is less than or equal to a given value in Numpy
To check which element in a masked array is less than or equal to a given value, use the ma.MaskedArray.__le__() method. Returns with boolean type i.e. True and False. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and ...
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